Time Series Analysis and Forecasting with the TSstudio Package

# Time Series Analysis and Forecasting with the TSstudio Package
## Bay Area R Users Group Meetup
### Rami Krispin
### 2018-12-11

---

## Agenda

- Introduction

- Utility functions

- Visualization tools

- Seasonal analysis

- Correlation analysis

- Forecasting applications

- Road map

---

## Any experince with time series analysis?

##forecast and plotly packages?

---
class: inverse

## Introduction

The **TSstudio** package provides a set of functions for time series analysis and forecasting such as:

- Utility functions for pre-processing time series data
- Interactive data visualization tools for descriptive analysis, based on the **plotly** package engine
- Set of functions for predictive analysis and forecasting automation with the use of models from the **forecast**, **forecastHybrid**, and **bsts** packages

The primary goal of the package is to simplify the analysis workflow (or, minimum code - maximum results)

---

## Package structure

![](TSstudio Structure.png)

---
class: inverse

# Installation

Install from [CRAN](https://cran.r-project.org/web/packages/TSstudio/index.html):

```r
install.packages("TSstudio")
```

Or from [Github](https://github.com/RamiKrispin/TSstudio):

```r
devtools::install_github("RamiKrispin/TSstudio")
```

---
class: inverse

# Utility functions - object info

The `ts_info` returns the main characteristics of the series:

```r
library(TSstudio)
data("USVSales")
ts_info(USgas)
```

```
##  The USgas series is a ts object with 1 variable and 225 observations
##  Frequency: 12 
##  Start time: 2000 1 
##  End time: 2018 9
```

```r
data("Michigan_CS")
ts_info(Michigan_CS)
```

```
##  The Michigan_CS series is a xts object with 1 variable and 465 observations
##  Frequency: monthly 
##  Start time: Jan 1980 
##  End time: Sep 2018
```

---
class: inverse

# Utility functions - creating partitions

The `ts_split` splits a time series object to a training and testing partitions:

```r
USgas_split <- ts_split(USgas, sample.out = 12)

train <- USgas_split$train
test <- USgas_split$test
```

---
class: inverse

# Utility functions - creating partitions

The `ts_split` splits a time series object to a training and testing partitions:

```r
ts_info(train)
```

```
##  The train series is a ts object with 1 variable and 213 observations
##  Frequency: 12 
##  Start time: 2000 1 
##  End time: 2017 9
```

```r
ts_info(test)
```

```
##  The test series is a ts object with 1 variable and 12 observations
##  Frequency: 12 
##  Start time: 2017 10 
##  End time: 2018 9
```

---
class: inverse

# Utility functions - prophet object

The `ts_to_prophet` convert time series object (e.g., `ts`, `xts`, `zoo`) to `prophet` input structure:

```r
USgas_prophet <- ts_to_prophet(USgas)

head(USgas_prophet)
```

```
##           ds      y
## 1 2000-01-01 2510.5
## 2 2000-02-01 2330.7
## 3 2000-03-01 2050.6
## 4 2000-04-01 1783.3
## 5 2000-05-01 1632.9
## 6 2000-06-01 1513.1
```

---
class: inverse

# Utility functions - more

Another useful utility functions:

- `xts_to_ts()` for converting `xts` object to `ts` object
- `zoo_to_ts()` for converting `zoo` object to `ts` object
- `ts_sum()` - summation of multiple time series objects
- `ts_reshape()` - transform time series object to a data frame format

---
class: inverse

# Visualization tools - plotting ts object

The `ts_plot` function plot time series objects, supporting multiple formats (i.e., `ts`, `xts`, `zoo`, `data.frame`, `tbl`):

```r
ts_plot(USgas)
```

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---
class: inverse

# Visualization tools - plotting ts object

It is fairly simple to customize the plot:

```r
ts_plot(USgas, Ytitle = "Billion Cubic Feet", 
        title = "Monthly Natural Gas Consumption in the US",
        slider = TRUE, color = "green") 
```

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---
class: inverse

# Visualization tools - add plotly layer

All the visualization outputs are `plotly` objects:

```r
p <- ts_plot(USgas, Ytitle = "Billion Cubic Feet", 
 title = "Monthly Natural Gas Consumption in the US")
class(p)
```

```
## [1] "plotly"     "htmlwidget"
```

---
class: inverse

# Visualization tools - add plotly layer

Therefore, you can apply any of the plotly functions, and customize the object accordingly:

```r
library(plotly)
p %>% layout(font = list(color = "black"),
       plot_bgcolor = "white", paper_bgcolor = "#f2f2f2")
```

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---
class: inverse

# Seasonal analysis

The package provides a set of functions for seasonal analysis, such as:

- `ts_seasonal()` - provides a view of the series by its frequency units, applicable for a series with daily frequency and above (e.g., monthly, quarterly)
- `ts_heatmap()` - heatmap for time series data supports time series with half hour frequency and above
- `ts_surface` - A 3D view of the series, by the frequency units (e.g., the month of the year), the cycle units (e.g. the year), and the series values
- `ts_polar` - polar plot of time series data, applicable for monthly or quarterly series
- `ts_quantile` - quantile plots of time series data

---
class: inverse

# Seasonal analysis - seasonal plots

```r
ts_seasonal(USgas, type = "all",
            palette_normal = "inferno")
```

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---
class: inverse

# Seasonal analysis - heatmap

```r
ts_heatmap(USgas, color = "Greens")
```

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---
class: inverse

# Seasonal analysis - 3D view

```r
ts_surface(USgas)
```

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---
class: inverse

# Correlation analysis - ACF plot

```r
ts_acf(USgas)
```

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---
class: inverse

# Correlation analysis - lags plot

```r
ts_lags(USgas)
```

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---
class: inverse

# Correlation analysis - lags plot

```r
ts_lags(USgas, lags = c(12, 24, 36, 48))
```

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---

# Forecasting applications - error evaluation

```r
library(forecast)

USgas_split <- ts_split(USgas, sample.out = 12)
train <- USgas_split$train
test <- USgas_split$test

md <- auto.arima(train, stepwise = FALSE, approximation = FALSE)
fc <- forecast(md, h = 12)

accuracy(fc, test)
```

```
##                     ME      RMSE       MAE        MPE     MAPE      MASE
## Training set  -1.66563  98.53365  72.04795 -0.2777977 3.497193 0.6743267
## Test set     174.92468 196.47007 174.92468  7.0405671 7.040567 1.6371928
##                     ACF1 Theil's U
## Training set  0.02073135        NA
## Test set     -0.15231904 0.5813516
```

---
class: inverse

# Forecasting applications - error evaluation

```r
test_forecast(actual = USgas, test = test, forecast.obj = fc)
```

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MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1653.1 Fitted Value: 1651.46 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1475 Fitted Value: 1473.54 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1567.8 Fitted Value: 1566.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1908.5 Fitted Value: 1906.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2587.5 Fitted Value: 2584.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2677 Fitted Value: 2576.73 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2309.5 Fitted Value: 2388.91 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2246.6 Fitted Value: 2089.98 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1807.2 Fitted Value: 1880.52 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1522.4 Fitted Value: 1610.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1444.4 Fitted Value: 1486.34 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1598.1 Fitted Value: 1542.66 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1669.2 Fitted Value: 1696.56 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1494.1 Fitted Value: 1486.64 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1649.1 Fitted Value: 1605.73 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1701 Fitted Value: 1898.14 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2120.2 Fitted Value: 2396.57 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2487.6 Fitted Value: 2491.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2242.4 Fitted Value: 2306.48 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2258.4 Fitted Value: 2131.87 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1881 Fitted Value: 1856.77 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1611.5 Fitted Value: 1600.37 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1591.4 Fitted Value: 1508.3 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1748.4 Fitted Value: 1635.49 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1725.7 Fitted Value: 1743.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1542.2 Fitted Value: 1518.18 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1645.9 Fitted Value: 1657.31 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1913.6 Fitted Value: 1846.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2378.9 Fitted Value: 2408.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2700.5 Fitted Value: 2608.53 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2500.3 Fitted Value: 2400 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2197.9 Fitted Value: 2295.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1743.5 Fitted Value: 1845.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1514.7 Fitted Value: 1595.97 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1368.4 Fitted Value: 1517.66 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1600.5 Fitted Value: 1595.1 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1651.6 Fitted Value: 1706.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1428.6 Fitted Value: 1498.27 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1553.2 Fitted Value: 1604.04 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1753.6 Fitted Value: 1824.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2263.7 Fitted Value: 2321.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2675.8 Fitted Value: 2586.48 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2511.1 Fitted Value: 2405.88 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2100.9 Fitted Value: 2255.4 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1745.2 Fitted Value: 1761.34 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1573 Fitted Value: 1577.32 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1483.7 Fitted Value: 1490.77 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1584.9 Fitted Value: 1631.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1578 Fitted Value: 1666.37 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1482.2 Fitted Value: 1456.26 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1557.2 Fitted Value: 1618.38 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1782.8 Fitted Value: 1797.78 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2327.7 Fitted Value: 2325.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2561.9 Fitted Value: 2627.58 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2243 Fitted Value: 2367.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2205.8 Fitted Value: 2121.49 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1724.9 Fitted Value: 1823.52 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1522.6 Fitted Value: 1530.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1534.1 Fitted Value: 1475.35 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1686.6 Fitted Value: 1642.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1695.1 Fitted Value: 1684.47 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1422.5 Fitted Value: 1504.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1428.2 Fitted Value: 1570.2 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1663.4 Fitted Value: 1751.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2326.4 Fitted Value: 2284.39 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2165.3 Fitted Value: 2610.28 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2144.4 Fitted Value: 2147.5 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2126.4 Fitted Value: 2126.57 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1681 Fitted Value: 1729.5 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1526.3 Fitted Value: 1495.7 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1550.9 Fitted Value: 1462.82 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1758.7 Fitted Value: 1636.2 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1751.7 Fitted Value: 1699.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1462.1 Fitted Value: 1492.51 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1644.2 Fitted Value: 1552.32 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1765.4 Fitted Value: 1827.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2122.8 Fitted Value: 2315.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2475.6 Fitted Value: 2446.75 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2567 Fitted Value: 2330.09 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2128.8 Fitted Value: 2281.57 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1810.1 Fitted Value: 1721.3 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1559.1 Fitted Value: 1613.36 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1555.2 Fitted Value: 1508.13 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1659.9 Fitted Value: 1701.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1896.1 Fitted Value: 1696.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1590.5 Fitted Value: 1596.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1627.8 Fitted Value: 1630.9 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1834.5 Fitted Value: 1834.83 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2399.2 Fitted Value: 2351.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2734 Fitted Value: 2601.04 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2503.4 Fitted Value: 2497.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2278.2 Fitted Value: 2253.51 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1823.9 Fitted Value: 1870.03 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1576.4 Fitted Value: 1627.18 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1604.2 Fitted Value: 1577.44 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1708.6 Fitted Value: 1750.65 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1682.9 Fitted Value: 1785.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1460.9 Fitted Value: 1525.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1635.8 Fitted Value: 1625.92 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1868.9 Fitted Value: 1857.38 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2399.7 Fitted Value: 2383.48 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2729.7 Fitted Value: 2632.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2332.5 Fitted Value: 2508.49 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2170.7 Fitted Value: 2187.55 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1741.3 Fitted Value: 1837.7 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1504 Fitted Value: 1580.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1527.8 Fitted Value: 1548.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1658 Fitted Value: 1703.05 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1736.5 Fitted Value: 1739.65 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1575 Fitted Value: 1530.15 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1666.5 Fitted Value: 1661.72 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1776.2 Fitted Value: 1857.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2491.9 Fitted Value: 2344.26 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2809.8 Fitted Value: 2702.58 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2481 Fitted Value: 2499.72 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2142.9 Fitted Value: 2256.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1691.8 Fitted Value: 1801.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1617.3 Fitted Value: 1569.04 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1649.5 Fitted Value: 1610.19 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1825.8 Fitted Value: 1748.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1878.9 Fitted Value: 1826.51 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1637.5 Fitted Value: 1610.56 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1664.9 Fitted Value: 1710.53 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1973.3 Fitted Value: 1872.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2714.1 Fitted Value: 2493.55 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2888.6 Fitted Value: 2831.05 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2452.4 Fitted Value: 2557.28 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2230.5 Fitted Value: 2266.29 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1825 Fitted Value: 1870.4 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1667.4 Fitted Value: 1664.01 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1657.3 Fitted Value: 1668.91 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1890.5 Fitted Value: 1804.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1891.8 Fitted Value: 1902.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1655.6 Fitted Value: 1648.55 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1744.5 Fitted Value: 1747.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2031.9 Fitted Value: 1954.83 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2541.9 Fitted Value: 2578.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2756.2 Fitted Value: 2786.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2500.7 Fitted Value: 2526.33 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2127.8 Fitted Value: 2303.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1953.1 Fitted Value: 1816.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1873.8 Fitted Value: 1751.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1868.4 Fitted Value: 1749.85 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2069.8 Fitted Value: 1920.19 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2008.8 Fitted Value: 1994.23 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1807.2 Fitted Value: 1726.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1901.1 Fitted Value: 1850.07 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2167.8 Fitted Value: 2068.45 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2503.9 Fitted Value: 2669.95 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2878.8 Fitted Value: 2802.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2567.2 Fitted Value: 2636.35 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2521.1 Fitted Value: 2330.5 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1967.5 Fitted Value: 2068.01 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1752.5 Fitted Value: 1780.06 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1742.9 Fitted Value: 1789.32 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1926.3 Fitted Value: 1939.69 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1927.4 Fitted Value: 1976.29 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1767 Fitted Value: 1738.16 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1866.8 Fitted Value: 1859.82 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2316.9 Fitted Value: 2082.98 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2920.8 Fitted Value: 2726.07 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3204.1 Fitted Value: 3002.93 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2741.2 Fitted Value: 2761.9 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2557.9 Fitted Value: 2466.3 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1961.7 Fitted Value: 2110.35 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1810.2 Fitted Value: 1826.05 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1745.4 Fitted Value: 1856.69 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1881 Fitted Value: 1974.44 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1933.1 Fitted Value: 1990.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1809.3 Fitted Value: 1784.88 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1912.8 Fitted Value: 1908.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2357.5 Fitted Value: 2166.4 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2679.2 Fitted Value: 2800.21 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3115 Fitted Value: 2945.06 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2925.2 Fitted Value: 2767.93 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2591.3 Fitted Value: 2572.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2007.9 Fitted Value: 2090.58 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1858.1 Fitted Value: 1867.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1899.9 Fitted Value: 1870.24 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2067.7 Fitted Value: 2047.68 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2052.7 Fitted Value: 2073.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1901.3 Fitted Value: 1858.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1987.3 Fitted Value: 1978.89 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2249.1 Fitted Value: 2260.23 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2588.2 Fitted Value: 2760.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3091.7 Fitted Value: 2977.33 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2652.3 Fitted Value: 2808.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2356.3 Fitted Value: 2464.93 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2083.8 Fitted Value: 2008.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1965.8 Fitted Value: 1909.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2000.7 Fitted Value: 1899.67 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2186.6 Fitted Value: 2090 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2208.4 Fitted Value: 2120.81 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1947.8 Fitted Value: 1938.46 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1925.2 Fitted Value: 2004.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2159.4 Fitted Value: 2250.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2866.3 Fitted Value: 2716.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2900.9 Fitted Value: 3146.46 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2329.1 Fitted Value: 2671.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2529.3 Fitted Value: 2354 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1927.9 Fitted Value: 2126.36 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1896.9 Fitted Value: 1808.98 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1912.1 Fitted Value: 1916.59 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2132.7 Fitted Value: 2050.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2104.9 Fitted Value: 2112.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1922.6 Fitted Value: 1880.23 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2036.9 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2351.3 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3065.8 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3307.6 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2699.1 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2771.7 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2335.3 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2045.6 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2049 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2341.1 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2312.6 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2084.1 Fitted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47"]},"167331774c0ec.2":{"alpha":1,"sizes":[10,100],"x":[2000,2000.08333333333,2000.16666666667,2000.25,2000.33333333333,2000.41666666667,2000.5,2000.58333333333,2000.66666666667,2000.75,2000.83333333333,2000.91666666667,2001,2001.08333333333,2001.16666666667,2001.25,2001.33333333333,2001.41666666667,2001.5,2001.58333333333,2001.66666666667,2001.75,2001.83333333333,2001.91666666667,2002,2002.08333333333,2002.16666666667,2002.25,2002.33333333333,2002.41666666667,2002.5,2002.58333333333,2002.66666666667,2002.75,2002.83333333333,2002.91666666667,2003,2003.08333333333,2003.16666666667,2003.25,2003.33333333333,2003.41666666667,2003.5,2003.58333333333,2003.66666666667,2003.75,2003.83333333333,2003.91666666667,2004,2004.08333333333,2004.16666666667,2004.25,2004.33333333333,2004.41666666667,2004.5,2004.58333333333,2004.66666666667,2004.75,2004.83333333333,2004.91666666667,2005,2005.08333333333,2005.16666666667,2005.25,2005.33333333333,2005.41666666667,2005.5,2005.58333333333,2005.66666666667,2005.75,2005.83333333333,2005.91666666667,2006,2006.08333333333,2006.16666666667,2006.25,2006.33333333333,2006.41666666667,2006.5,2006.58333333333,2006.66666666667,2006.75,2006.83333333333,2006.91666666667,2007,2007.08333333333,2007.16666666667,2007.25,2007.33333333333,2007.41666666667,2007.5,2007.58333333333,2007.66666666667,2007.75,2007.83333333333,2007.91666666667,2008,2008.08333333333,2008.16666666667,2008.25,2008.33333333333,2008.41666666667,2008.5,2008.58333333333,2008.66666666667,2008.75,2008.83333333333,2008.91666666667,2009,2009.08333333333,2009.16666666667,2009.25,2009.33333333333,2009.41666666667,2009.5,2009.58333333333,2009.66666666667,2009.75,2009.83333333333,2009.91666666667,2010,2010.08333333333,2010.16666666667,2010.25,2010.33333333333,2010.41666666667,2010.5,2010.58333333333,2010.66666666667,2010.75,2010.83333333333,2010.91666666667,2011,2011.08333333333,2011.16666666667,2011.25,2011.33333333333,2011.41666666667,2011.5,2011.58333333333,2011.66666666667,2011.75,2011.83333333333,2011.91666666667,2012,2012.08333333333,2012.16666666667,2012.25,2012.33333333333,2012.41666666667,2012.5,2012.58333333333,2012.66666666667,2012.75,2012.83333333333,2012.91666666667,2013,2013.08333333333,2013.16666666667,2013.25,2013.33333333333,2013.41666666667,2013.5,2013.58333333333,2013.66666666667,2013.75,2013.83333333333,2013.91666666667,2014,2014.08333333333,2014.16666666667,2014.25,2014.33333333333,2014.41666666667,2014.5,2014.58333333333,2014.66666666667,2014.75,2014.83333333333,2014.91666666667,2015,2015.08333333333,2015.16666666667,2015.25,2015.33333333333,2015.41666666667,2015.5,2015.58333333333,2015.66666666667,2015.75,2015.83333333333,2015.91666666667,2016,2016.08333333333,2016.16666666667,2016.25,2016.33333333333,2016.41666666667,2016.5,2016.58333333333,2016.66666666667,2016.75,2016.83333333333,2016.91666666667,2017,2017.08333333333,2017.16666666667,2017.25,2017.33333333333,2017.41666666667,2017.5,2017.58333333333,2017.66666666667,2017.75,2017.83333333333,2017.91666666667,2018,2018.08333333333,2018.16666666667,2018.25,2018.33333333333,2018.41666666667,2018.5,2018.58333333333,2018.66666666667],"y":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1977.70539512569,2242.9826055328,2761.47330180799,3043.53637505374,2695.37762673883,2525.05599495104,2068.86259944481,1926.58787475071,1926.44587054045,2101.278080207,2114.64398849022,1917.0541381848],"mode":"lines+markers","name":"Forecasted","type":"scatter","hoverinfo":"text","text":["Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2510.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2330.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2050.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1783.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1632.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1513.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1525.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1653.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1475 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1567.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1908.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2587.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2677 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2309.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2246.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1807.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1522.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1444.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1598.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1669.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1494.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1649.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1701 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2120.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2487.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2242.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2258.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1881 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1611.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1591.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1748.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1725.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1542.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1645.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1913.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2378.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2700.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2500.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2197.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1743.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1514.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1368.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1600.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1651.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1428.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1553.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1753.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2263.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2675.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2511.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2100.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1745.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1573 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1483.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1584.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1578 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1482.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1557.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1782.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2327.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2561.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2243 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2205.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1724.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1522.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1534.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1686.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1695.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1422.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1428.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1663.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2326.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2165.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2144.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2126.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1681 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1526.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1550.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1758.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1751.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1462.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1644.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1765.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2122.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2475.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2567 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2128.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1810.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1559.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1555.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1659.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1896.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1590.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1627.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1834.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2399.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2734 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2503.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2278.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1823.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1576.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1604.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1708.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1682.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1460.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1635.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1868.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2399.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2729.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2332.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2170.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1741.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1504 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1527.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1658 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1736.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1575 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1666.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1776.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2491.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2809.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2481 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2142.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1691.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1617.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1649.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1825.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1878.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1637.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1664.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1973.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2714.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2888.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2452.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2230.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1825 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1667.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1657.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1890.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1891.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1655.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1744.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2031.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2541.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2756.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2500.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2127.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1953.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1873.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1868.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2069.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2008.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1807.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1901.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2167.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2503.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2878.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2567.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2521.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1967.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1752.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1742.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1926.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1927.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1767 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1866.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2316.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2920.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3204.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2741.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2557.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1961.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1810.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1745.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1881 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1933.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1809.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1912.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2357.5 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2679.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3115 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2925.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2591.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2007.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1858.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1899.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2067.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2052.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1901.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1987.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2249.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2588.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3091.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2652.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2356.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2083.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1965.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2000.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2186.6 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2208.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1947.8 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1925.2 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2159.4 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2866.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2900.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2329.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2529.3 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1927.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1896.9 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1912.1 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2132.7 Forecasted Value: NA Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2104.9 Forecasted Value: NA 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ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2510.5 Fitted Value: 2507.99 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2330.7 Fitted Value: 2328.37 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2050.6 Fitted Value: 2048.56 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1783.3 Fitted Value: 1781.52 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1632.9 Fitted Value: 1631.28 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1513.1 Fitted Value: 1511.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1525.6 Fitted Value: 1524.09 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1653.1 Fitted Value: 1651.46 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1475 Fitted Value: 1473.54 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1567.8 Fitted Value: 1566.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1908.5 Fitted Value: 1906.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2587.5 Fitted Value: 2584.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2677 Fitted Value: 2576.73 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2309.5 Fitted Value: 2388.91 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2246.6 Fitted Value: 2089.98 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1807.2 Fitted Value: 1880.52 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1522.4 Fitted Value: 1610.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1444.4 Fitted Value: 1486.34 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1598.1 Fitted Value: 1542.66 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1669.2 Fitted Value: 1696.56 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1494.1 Fitted Value: 1486.64 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1649.1 Fitted Value: 1605.73 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1701 Fitted Value: 1898.14 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2120.2 Fitted Value: 2396.57 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2487.6 Fitted Value: 2491.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2242.4 Fitted Value: 2306.48 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2258.4 Fitted Value: 2131.87 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1881 Fitted Value: 1856.77 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1611.5 Fitted Value: 1600.37 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1591.4 Fitted Value: 1508.3 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1748.4 Fitted Value: 1635.49 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1725.7 Fitted Value: 1743.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1542.2 Fitted Value: 1518.18 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1645.9 Fitted Value: 1657.31 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1913.6 Fitted Value: 1846.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2378.9 Fitted Value: 2408.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2700.5 Fitted Value: 2608.53 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2500.3 Fitted Value: 2400 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2197.9 Fitted Value: 2295.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1743.5 Fitted Value: 1845.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1514.7 Fitted Value: 1595.97 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1368.4 Fitted Value: 1517.66 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1600.5 Fitted Value: 1595.1 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1651.6 Fitted Value: 1706.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1428.6 Fitted Value: 1498.27 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1553.2 Fitted Value: 1604.04 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1753.6 Fitted Value: 1824.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2263.7 Fitted Value: 2321.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2675.8 Fitted Value: 2586.48 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2511.1 Fitted Value: 2405.88 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2100.9 Fitted Value: 2255.4 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1745.2 Fitted Value: 1761.34 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1573 Fitted Value: 1577.32 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1483.7 Fitted Value: 1490.77 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1584.9 Fitted Value: 1631.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1578 Fitted Value: 1666.37 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1482.2 Fitted Value: 1456.26 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1557.2 Fitted Value: 1618.38 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1782.8 Fitted Value: 1797.78 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2327.7 Fitted Value: 2325.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2561.9 Fitted Value: 2627.58 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2243 Fitted Value: 2367.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2205.8 Fitted Value: 2121.49 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1724.9 Fitted Value: 1823.52 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1522.6 Fitted Value: 1530.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1534.1 Fitted Value: 1475.35 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1686.6 Fitted Value: 1642.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1695.1 Fitted Value: 1684.47 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1422.5 Fitted Value: 1504.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1428.2 Fitted Value: 1570.2 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1663.4 Fitted Value: 1751.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2326.4 Fitted Value: 2284.39 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2165.3 Fitted Value: 2610.28 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2144.4 Fitted Value: 2147.5 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2126.4 Fitted Value: 2126.57 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1681 Fitted Value: 1729.5 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1526.3 Fitted Value: 1495.7 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1550.9 Fitted Value: 1462.82 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1758.7 Fitted Value: 1636.2 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1751.7 Fitted Value: 1699.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1462.1 Fitted Value: 1492.51 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1644.2 Fitted Value: 1552.32 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1765.4 Fitted Value: 1827.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2122.8 Fitted Value: 2315.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2475.6 Fitted Value: 2446.75 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2567 Fitted Value: 2330.09 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2128.8 Fitted Value: 2281.57 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1810.1 Fitted Value: 1721.3 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1559.1 Fitted Value: 1613.36 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1555.2 Fitted Value: 1508.13 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1659.9 Fitted Value: 1701.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1896.1 Fitted Value: 1696.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1590.5 Fitted Value: 1596.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1627.8 Fitted Value: 1630.9 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1834.5 Fitted Value: 1834.83 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2399.2 Fitted Value: 2351.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2734 Fitted Value: 2601.04 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2503.4 Fitted Value: 2497.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2278.2 Fitted Value: 2253.51 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1823.9 Fitted Value: 1870.03 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1576.4 Fitted Value: 1627.18 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1604.2 Fitted Value: 1577.44 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1708.6 Fitted Value: 1750.65 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1682.9 Fitted Value: 1785.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1460.9 Fitted Value: 1525.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1635.8 Fitted Value: 1625.92 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1868.9 Fitted Value: 1857.38 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2399.7 Fitted Value: 2383.48 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2729.7 Fitted Value: 2632.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2332.5 Fitted Value: 2508.49 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2170.7 Fitted Value: 2187.55 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1741.3 Fitted Value: 1837.7 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1504 Fitted Value: 1580.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1527.8 Fitted Value: 1548.86 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1658 Fitted Value: 1703.05 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1736.5 Fitted Value: 1739.65 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1575 Fitted Value: 1530.15 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1666.5 Fitted Value: 1661.72 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1776.2 Fitted Value: 1857.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2491.9 Fitted Value: 2344.26 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2809.8 Fitted Value: 2702.58 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2481 Fitted Value: 2499.72 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2142.9 Fitted Value: 2256.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1691.8 Fitted Value: 1801.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1617.3 Fitted Value: 1569.04 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1649.5 Fitted Value: 1610.19 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1825.8 Fitted Value: 1748.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1878.9 Fitted Value: 1826.51 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1637.5 Fitted Value: 1610.56 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1664.9 Fitted Value: 1710.53 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1973.3 Fitted Value: 1872.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2714.1 Fitted Value: 2493.55 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2888.6 Fitted Value: 2831.05 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2452.4 Fitted Value: 2557.28 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2230.5 Fitted Value: 2266.29 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1825 Fitted Value: 1870.4 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1667.4 Fitted Value: 1664.01 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1657.3 Fitted Value: 1668.91 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1890.5 Fitted Value: 1804.62 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1891.8 Fitted Value: 1902.84 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1655.6 Fitted Value: 1648.55 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1744.5 Fitted Value: 1747.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2031.9 Fitted Value: 1954.83 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2541.9 Fitted Value: 2578.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2756.2 Fitted Value: 2786.94 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2500.7 Fitted Value: 2526.33 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2127.8 Fitted Value: 2303.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1953.1 Fitted Value: 1816.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1873.8 Fitted Value: 1751.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1868.4 Fitted Value: 1749.85 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2069.8 Fitted Value: 1920.19 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2008.8 Fitted Value: 1994.23 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1807.2 Fitted Value: 1726.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1901.1 Fitted Value: 1850.07 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2167.8 Fitted Value: 2068.45 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2503.9 Fitted Value: 2669.95 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2878.8 Fitted Value: 2802.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2567.2 Fitted Value: 2636.35 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2521.1 Fitted Value: 2330.5 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1967.5 Fitted Value: 2068.01 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1752.5 Fitted Value: 1780.06 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1742.9 Fitted Value: 1789.32 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1926.3 Fitted Value: 1939.69 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1927.4 Fitted Value: 1976.29 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1767 Fitted Value: 1738.16 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1866.8 Fitted Value: 1859.82 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2316.9 Fitted Value: 2082.98 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2920.8 Fitted Value: 2726.07 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3204.1 Fitted Value: 3002.93 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2741.2 Fitted Value: 2761.9 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2557.9 Fitted Value: 2466.3 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1961.7 Fitted Value: 2110.35 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1810.2 Fitted Value: 1826.05 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1745.4 Fitted Value: 1856.69 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1881 Fitted Value: 1974.44 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1933.1 Fitted Value: 1990.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1809.3 Fitted Value: 1784.88 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1912.8 Fitted Value: 1908.25 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2357.5 Fitted Value: 2166.4 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2679.2 Fitted Value: 2800.21 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3115 Fitted Value: 2945.06 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2925.2 Fitted Value: 2767.93 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2591.3 Fitted Value: 2572.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2007.9 Fitted Value: 2090.58 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1858.1 Fitted Value: 1867.6 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1899.9 Fitted Value: 1870.24 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2067.7 Fitted Value: 2047.68 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2052.7 Fitted Value: 2073.11 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1901.3 Fitted Value: 1858.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1987.3 Fitted Value: 1978.89 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2249.1 Fitted Value: 2260.23 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2588.2 Fitted Value: 2760.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 3091.7 Fitted Value: 2977.33 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2652.3 Fitted Value: 2808.76 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2356.3 Fitted Value: 2464.93 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2083.8 Fitted Value: 2008.61 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1965.8 Fitted Value: 1909.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2000.7 Fitted Value: 1899.67 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2186.6 Fitted Value: 2090 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2208.4 Fitted Value: 2120.81 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1947.8 Fitted Value: 1938.46 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1925.2 Fitted Value: 2004.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2159.4 Fitted Value: 2250.63 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2866.3 Fitted Value: 2716.8 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2900.9 Fitted Value: 3146.46 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2329.1 Fitted Value: 2671.17 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2529.3 Fitted Value: 2354 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1927.9 Fitted Value: 2126.36 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1896.9 Fitted Value: 1808.98 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1912.1 Fitted Value: 1916.59 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2132.7 Fitted Value: 2050.74 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 2104.9 Fitted Value: 2112.43 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47","Model: ARIMA(1,0,2)(0,1,1)[12] with drift Actual: 1922.6 Fitted Value: 1880.23 Training Set MAPE: 3.5 RMSE: 98.53 Testing Set MAPE: 7.04 RMSE: 196.47"],"xaxis":"x","yaxis":"y","frame":null},{"x":[2017.75,2017.83333333333,2017.91666666667,2018,2018.08333333333,2018.16666666667,2018.25,2018.33333333333,2018.41666666667,2018.5,2018.58333333333,2018.66666666667],"y":[1977.70539512569,2242.9826055328,2761.47330180799,3043.53637505374,2695.37762673883,2525.05599495104,2068.86259944481,1926.58787475071,1926.44587054045,2101.278080207,2114.64398849022,1917.0541381848],"mode":"lines+markers","name":"Forecasted","type":"scatter","hoverinfo":["text","text","text","text","text","text","text","text","text","text","text","text"],"text":["Model: ARIMA(1,0,2)(0,1,1)[12] with drift 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---
class: inverse

# Forecasting applications - forecast plot

```r
md1 <- auto.arima(USgas, stepwise = FALSE, approximation = FALSE)
fc1 <- forecast(md1, h = 60)
plot_forecast(fc1)
```

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---
class: inverse

# Forecasting applications - backtesting
<img src="backtesting.png" width="500px" />

[Source - Uber Engineering Blog](https://eng.uber.com/omphalos/)

---
class: inverse