South ural state university, Chelyabinsk, Russian federation
#Import
library(fpp2)
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
## -- Attaching packages ---------------------------------------------- fpp2 2.4 --
## v ggplot2 3.3.2 v fma 2.4
## v forecast 8.13 v expsmooth 2.3
##
library(forecast)
library(ggplot2)
library("readxl")
library(moments)
library(forecast)
require(forecast)
require(tseries)
## Loading required package: tseries
require(markovchain)
## Loading required package: markovchain
## Package: markovchain
## Version: 0.8.5-3
## Date: 2020-12-03
## BugReport: https://github.com/spedygiorgio/markovchain/issues
require(data.table)
## Loading required package: data.table
library(Hmisc)
## Loading required package: lattice
## Loading required package: survival
## Loading required package: Formula
##
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:base':
##
## format.pval, units
library(ascii)
##Global vriable##
Full_original_data <- read.csv("data.csv") # path of your data ( time series data)
original_data<-Full_original_data$cases
y_lab <- "Forecast Third wave infection cases in Russia" # input name of data
Actual_date_interval <- c("2020/03/01","2021/04/22")
Forecast_date_interval <- c("2021/04/23","2021/07/30")
validation_data_days <-50
frequency<-"days"
Number_Neural<-30 # Number of Neural For model NNAR Model
NNAR_Model<- TRUE #create new model (TRUE/FALSE)
frequency<-"days"
# Data Preparation & calculate some of statistics measures
summary(original_data) # Summary your time series
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0 4866 8388 9950 14876 29935
# calculate standard deviation
data.frame(kurtosis=kurtosis(original_data)) # calculate Cofficient of kurtosis
## kurtosis
## 1 2.630336
data.frame(skewness=skewness(original_data)) # calculate Cofficient of skewness
## skewness
## 1 0.7716437
data.frame(Standard.deviation =sd(original_data))
## Standard.deviation
## 1 8379.285
#processing on data (input data)
rows <- NROW(original_data) # calculate number of rows in time series (number of days)
training_data<-original_data[1:(rows-validation_data_days)] # Training data
testing_data<-original_data[(rows-validation_data_days+1):rows] #testing data
AD<-fulldate<-seq(as.Date(Actual_date_interval[1]),as.Date(Actual_date_interval[2]), frequency) #input range for actual date
FD<-seq(as.Date(Forecast_date_interval[1]),as.Date(Forecast_date_interval[2]), frequency) #input range forecasting date
N_forecasting_days<-nrow(data.frame(FD)) #calculate number of days that you want to forecasting
validation_dates<-tail(AD,validation_data_days) # select validation_dates
validation_data_by_name<-weekdays(validation_dates) # put names of validation dates
forecasting_data_by_name<-weekdays(FD) # put names of Forecasting dates
#NNAR Model
if(NNAR_Model==TRUE){
data_series<-ts(training_data)
model_NNAR<-nnetar(data_series, size = Number_Neural)
saveRDS(model_NNAR, file = "model_NNAR.RDS")
my_model <- readRDS("model_NNAR.RDS")
accuracy(model_NNAR) # accuracy on training data #Print Model Parameters
model_NNAR
}
## Series: data_series
## Model: NNAR(22,30)
## Call: nnetar(y = data_series, size = Number_Neural)
##
## Average of 20 networks, each of which is
## a 22-30-1 network with 721 weights
## options were - linear output units
##
## sigma^2 estimated as 62621
if(NNAR_Model==FALSE){
data_series<-ts(training_data)
#model_NNAR<-nnetar(data_series, size = Number_Numeral)
model_NNAR <- readRDS("model_NNAR.RDS")
accuracy(model_NNAR) # accuracy on training data #Print Model Parameters
model_NNAR
}
# Testing Data Evaluation
forecasting_NNAR <- forecast(model_NNAR, h=N_forecasting_days+validation_data_days)
validation_forecast<-head(forecasting_NNAR$mean,validation_data_days)
MAPE_Per_Day<-round( abs(((testing_data-validation_forecast)/testing_data)*100) ,3)
paste ("MAPE % For ",validation_data_days,frequency,"by using NNAR Model for ==> ",y_lab, sep=" ")
## [1] "MAPE % For 50 days by using NNAR Model for ==> Forecast Third wave infection cases in Russia"
MAPE_Mean_All<-paste(round(mean(MAPE_Per_Day),3),"% MAPE ",validation_data_days,frequency,y_lab,sep=" ")
MAPE_Mean_All_NNAR<-round(mean(MAPE_Per_Day),3)
MAPE_NNAR<-paste(round(MAPE_Per_Day,3),"%")
MAPE_NNAR_Model<-paste(MAPE_Per_Day ,"%")
paste (" MAPE that's Error of Forecasting for ",validation_data_days," days in NNAR Model for ==> ",y_lab, sep=" ")
## [1] " MAPE that's Error of Forecasting for 50 days in NNAR Model for ==> Forecast Third wave infection cases in Russia"
paste(MAPE_Mean_All,"%")
## [1] "60.485 % MAPE 50 days Forecast Third wave infection cases in Russia %"
paste ("MAPE that's Error of Forecasting day by day for ",validation_data_days," days in NNAR Model for ==> ",y_lab, sep=" ")
## [1] "MAPE that's Error of Forecasting day by day for 50 days in NNAR Model for ==> Forecast Third wave infection cases in Russia"
print(ascii(data.frame(date_NNAR=validation_dates,validation_data_by_name,actual_data=testing_data,forecasting_NNAR=validation_forecast,MAPE_NNAR_Model)), type = "rest")
##
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | | date_NNAR | validation_data_by_name | actual_data | forecasting_NNAR | MAPE_NNAR_Model |
## +====+============+=========================+=============+==================+=================+
## | 1 | 2021-03-04 | Thursday | 11385.00 | 10616.70 | 6.748 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 2 | 2021-03-05 | Friday | 11024.00 | 10605.53 | 3.796 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 3 | 2021-03-06 | Saturday | 11022.00 | 10433.45 | 5.34 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 4 | 2021-03-07 | Sunday | 10595.00 | 10527.88 | 0.634 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 5 | 2021-03-08 | Monday | 10253.00 | 10357.17 | 1.016 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 6 | 2021-03-09 | Tuesday | 9445.00 | 10306.90 | 9.125 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 7 | 2021-03-10 | Wednesday | 9079.00 | 10297.66 | 13.423 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 8 | 2021-03-11 | Thursday | 9270.00 | 10328.36 | 11.417 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 9 | 2021-03-12 | Friday | 9794.00 | 10374.34 | 5.925 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 10 | 2021-03-13 | Saturday | 9908.00 | 10429.67 | 5.265 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 11 | 2021-03-14 | Sunday | 10083.00 | 10540.34 | 4.536 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 12 | 2021-03-15 | Monday | 9437.00 | 10659.97 | 12.959 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 13 | 2021-03-16 | Tuesday | 9393.00 | 10442.74 | 11.176 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 14 | 2021-03-17 | Wednesday | 8998.00 | 10442.65 | 16.055 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 15 | 2021-03-18 | Thursday | 9803.00 | 10602.94 | 8.16 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 16 | 2021-03-19 | Friday | 9699.00 | 10890.91 | 12.289 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 17 | 2021-03-20 | Saturday | 9632.00 | 11276.10 | 17.069 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 18 | 2021-03-21 | Sunday | 9299.00 | 11412.09 | 22.724 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 19 | 2021-03-22 | Monday | 9284.00 | 11627.13 | 25.238 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 20 | 2021-03-23 | Tuesday | 8457.00 | 11784.40 | 39.345 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 21 | 2021-03-24 | Wednesday | 8861.00 | 12384.32 | 39.762 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 22 | 2021-03-25 | Thursday | 9221.00 | 12944.42 | 40.38 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 23 | 2021-03-26 | Friday | 9167.00 | 13530.38 | 47.599 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 24 | 2021-03-27 | Saturday | 8885.00 | 14154.72 | 59.31 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 25 | 2021-03-28 | Sunday | 9088.00 | 14741.32 | 62.206 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 26 | 2021-03-29 | Monday | 8711.00 | 15044.27 | 72.704 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 27 | 2021-03-30 | Tuesday | 8277.00 | 15198.37 | 83.622 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 28 | 2021-03-31 | Wednesday | 8275.00 | 15376.69 | 85.821 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 29 | 2021-04-01 | Thursday | 9169.00 | 15626.41 | 70.427 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 30 | 2021-04-02 | Friday | 8792.00 | 15837.71 | 80.138 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 31 | 2021-04-03 | Saturday | 9021.00 | 16208.24 | 79.672 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 32 | 2021-04-04 | Sunday | 8817.00 | 16498.42 | 87.121 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 33 | 2021-04-05 | Monday | 8646.00 | 16533.13 | 91.223 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 34 | 2021-04-06 | Tuesday | 8328.00 | 16446.72 | 97.487 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 35 | 2021-04-07 | Wednesday | 8294.00 | 16579.59 | 99.899 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 36 | 2021-04-08 | Thursday | 8672.00 | 16680.02 | 92.343 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 37 | 2021-04-09 | Friday | 9150.00 | 16796.86 | 83.572 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 38 | 2021-04-10 | Saturday | 8704.00 | 17005.82 | 95.379 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 39 | 2021-04-11 | Sunday | 8702.00 | 17118.12 | 96.715 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 40 | 2021-04-12 | Monday | 8320.00 | 17250.72 | 107.34 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 41 | 2021-04-13 | Tuesday | 8173.00 | 17477.12 | 113.84 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 42 | 2021-04-14 | Wednesday | 8326.00 | 17876.62 | 114.708 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 43 | 2021-04-15 | Thursday | 8944.00 | 18258.28 | 104.14 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 44 | 2021-04-16 | Friday | 8995.00 | 18619.73 | 107.001 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 45 | 2021-04-17 | Saturday | 9321.00 | 19074.92 | 104.645 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 46 | 2021-04-18 | Sunday | 8632.00 | 19514.25 | 126.069 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 47 | 2021-04-19 | Monday | 8589.00 | 19776.87 | 130.258 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 48 | 2021-04-20 | Tuesday | 8164.00 | 19979.38 | 144.725 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 49 | 2021-04-21 | Wednesday | 8271.00 | 20288.79 | 145.3 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
## | 50 | 2021-04-22 | Thursday | 8996.00 | 20567.01 | 128.624 % |
## +----+------------+-------------------------+-------------+------------------+-----------------+
print(ascii(data.frame(FD,forecating_date=forecasting_data_by_name,forecasting_by_NNAR=tail(forecasting_NNAR$mean,N_forecasting_days))), type = "rest")
##
## +----+------------+-----------------+---------------------+
## | | FD | forecating_date | forecasting_by_NNAR |
## +====+============+=================+=====================+
## | 1 | 2021-04-23 | Friday | 20789.78 |
## +----+------------+-----------------+---------------------+
## | 2 | 2021-04-24 | Saturday | 21212.14 |
## +----+------------+-----------------+---------------------+
## | 3 | 2021-04-25 | Sunday | 21540.34 |
## +----+------------+-----------------+---------------------+
## | 4 | 2021-04-26 | Monday | 21630.66 |
## +----+------------+-----------------+---------------------+
## | 5 | 2021-04-27 | Tuesday | 21745.73 |
## +----+------------+-----------------+---------------------+
## | 6 | 2021-04-28 | Wednesday | 22059.88 |
## +----+------------+-----------------+---------------------+
## | 7 | 2021-04-29 | Thursday | 22349.55 |
## +----+------------+-----------------+---------------------+
## | 8 | 2021-04-30 | Friday | 22664.17 |
## +----+------------+-----------------+---------------------+
## | 9 | 2021-05-01 | Saturday | 23082.64 |
## +----+------------+-----------------+---------------------+
## | 10 | 2021-05-02 | Sunday | 23409.91 |
## +----+------------+-----------------+---------------------+
## | 11 | 2021-05-03 | Monday | 23590.98 |
## +----+------------+-----------------+---------------------+
## | 12 | 2021-05-04 | Tuesday | 23829.58 |
## +----+------------+-----------------+---------------------+
## | 13 | 2021-05-05 | Wednesday | 24213.67 |
## +----+------------+-----------------+---------------------+
## | 14 | 2021-05-06 | Thursday | 24600.42 |
## +----+------------+-----------------+---------------------+
## | 15 | 2021-05-07 | Friday | 24971.74 |
## +----+------------+-----------------+---------------------+
## | 16 | 2021-05-08 | Saturday | 25456.38 |
## +----+------------+-----------------+---------------------+
## | 17 | 2021-05-09 | Sunday | 25816.15 |
## +----+------------+-----------------+---------------------+
## | 18 | 2021-05-10 | Monday | 25950.77 |
## +----+------------+-----------------+---------------------+
## | 19 | 2021-05-11 | Tuesday | 26082.05 |
## +----+------------+-----------------+---------------------+
## | 20 | 2021-05-12 | Wednesday | 26367.28 |
## +----+------------+-----------------+---------------------+
## | 21 | 2021-05-13 | Thursday | 26661.23 |
## +----+------------+-----------------+---------------------+
## | 22 | 2021-05-14 | Friday | 26964.47 |
## +----+------------+-----------------+---------------------+
## | 23 | 2021-05-15 | Saturday | 27326.05 |
## +----+------------+-----------------+---------------------+
## | 24 | 2021-05-16 | Sunday | 27529.08 |
## +----+------------+-----------------+---------------------+
## | 25 | 2021-05-17 | Monday | 27542.90 |
## +----+------------+-----------------+---------------------+
## | 26 | 2021-05-18 | Tuesday | 27578.16 |
## +----+------------+-----------------+---------------------+
## | 27 | 2021-05-19 | Wednesday | 27749.68 |
## +----+------------+-----------------+---------------------+
## | 28 | 2021-05-20 | Thursday | 27971.33 |
## +----+------------+-----------------+---------------------+
## | 29 | 2021-05-21 | Friday | 28221.38 |
## +----+------------+-----------------+---------------------+
## | 30 | 2021-05-22 | Saturday | 28485.30 |
## +----+------------+-----------------+---------------------+
## | 31 | 2021-05-23 | Sunday | 28640.71 |
## +----+------------+-----------------+---------------------+
## | 32 | 2021-05-24 | Monday | 28694.76 |
## +----+------------+-----------------+---------------------+
## | 33 | 2021-05-25 | Tuesday | 28739.41 |
## +----+------------+-----------------+---------------------+
## | 34 | 2021-05-26 | Wednesday | 28859.38 |
## +----+------------+-----------------+---------------------+
## | 35 | 2021-05-27 | Thursday | 29048.70 |
## +----+------------+-----------------+---------------------+
## | 36 | 2021-05-28 | Friday | 29269.78 |
## +----+------------+-----------------+---------------------+
## | 37 | 2021-05-29 | Saturday | 29485.09 |
## +----+------------+-----------------+---------------------+
## | 38 | 2021-05-30 | Sunday | 29562.25 |
## +----+------------+-----------------+---------------------+
## | 39 | 2021-05-31 | Monday | 29532.85 |
## +----+------------+-----------------+---------------------+
## | 40 | 2021-06-01 | Tuesday | 29487.78 |
## +----+------------+-----------------+---------------------+
## | 41 | 2021-06-02 | Wednesday | 29493.56 |
## +----+------------+-----------------+---------------------+
## | 42 | 2021-06-03 | Thursday | 29504.17 |
## +----+------------+-----------------+---------------------+
## | 43 | 2021-06-04 | Friday | 29508.12 |
## +----+------------+-----------------+---------------------+
## | 44 | 2021-06-05 | Saturday | 29474.59 |
## +----+------------+-----------------+---------------------+
## | 45 | 2021-06-06 | Sunday | 29314.48 |
## +----+------------+-----------------+---------------------+
## | 46 | 2021-06-07 | Monday | 29097.77 |
## +----+------------+-----------------+---------------------+
## | 47 | 2021-06-08 | Tuesday | 28907.29 |
## +----+------------+-----------------+---------------------+
## | 48 | 2021-06-09 | Wednesday | 28748.63 |
## +----+------------+-----------------+---------------------+
## | 49 | 2021-06-10 | Thursday | 28582.44 |
## +----+------------+-----------------+---------------------+
## | 50 | 2021-06-11 | Friday | 28408.46 |
## +----+------------+-----------------+---------------------+
## | 51 | 2021-06-12 | Saturday | 28215.28 |
## +----+------------+-----------------+---------------------+
## | 52 | 2021-06-13 | Sunday | 27968.64 |
## +----+------------+-----------------+---------------------+
## | 53 | 2021-06-14 | Monday | 27735.52 |
## +----+------------+-----------------+---------------------+
## | 54 | 2021-06-15 | Tuesday | 27571.28 |
## +----+------------+-----------------+---------------------+
## | 55 | 2021-06-16 | Wednesday | 27516.80 |
## +----+------------+-----------------+---------------------+
## | 56 | 2021-06-17 | Thursday | 27542.86 |
## +----+------------+-----------------+---------------------+
## | 57 | 2021-06-18 | Friday | 27577.05 |
## +----+------------+-----------------+---------------------+
## | 58 | 2021-06-19 | Saturday | 27602.63 |
## +----+------------+-----------------+---------------------+
## | 59 | 2021-06-20 | Sunday | 27611.65 |
## +----+------------+-----------------+---------------------+
## | 60 | 2021-06-21 | Monday | 27654.76 |
## +----+------------+-----------------+---------------------+
## | 61 | 2021-06-22 | Tuesday | 27749.89 |
## +----+------------+-----------------+---------------------+
## | 62 | 2021-06-23 | Wednesday | 27888.66 |
## +----+------------+-----------------+---------------------+
## | 63 | 2021-06-24 | Thursday | 27980.85 |
## +----+------------+-----------------+---------------------+
## | 64 | 2021-06-25 | Friday | 27981.47 |
## +----+------------+-----------------+---------------------+
## | 65 | 2021-06-26 | Saturday | 27887.62 |
## +----+------------+-----------------+---------------------+
## | 66 | 2021-06-27 | Sunday | 27675.11 |
## +----+------------+-----------------+---------------------+
## | 67 | 2021-06-28 | Monday | 27421.28 |
## +----+------------+-----------------+---------------------+
## | 68 | 2021-06-29 | Tuesday | 27187.18 |
## +----+------------+-----------------+---------------------+
## | 69 | 2021-06-30 | Wednesday | 26983.14 |
## +----+------------+-----------------+---------------------+
## | 70 | 2021-07-01 | Thursday | 26781.88 |
## +----+------------+-----------------+---------------------+
## | 71 | 2021-07-02 | Friday | 26564.89 |
## +----+------------+-----------------+---------------------+
## | 72 | 2021-07-03 | Saturday | 26308.62 |
## +----+------------+-----------------+---------------------+
## | 73 | 2021-07-04 | Sunday | 26011.54 |
## +----+------------+-----------------+---------------------+
## | 74 | 2021-07-05 | Monday | 25773.98 |
## +----+------------+-----------------+---------------------+
## | 75 | 2021-07-06 | Tuesday | 25664.86 |
## +----+------------+-----------------+---------------------+
## | 76 | 2021-07-07 | Wednesday | 25709.30 |
## +----+------------+-----------------+---------------------+
## | 77 | 2021-07-08 | Thursday | 25881.61 |
## +----+------------+-----------------+---------------------+
## | 78 | 2021-07-09 | Friday | 26142.57 |
## +----+------------+-----------------+---------------------+
## | 79 | 2021-07-10 | Saturday | 26505.91 |
## +----+------------+-----------------+---------------------+
## | 80 | 2021-07-11 | Sunday | 26967.74 |
## +----+------------+-----------------+---------------------+
## | 81 | 2021-07-12 | Monday | 27475.27 |
## +----+------------+-----------------+---------------------+
## | 82 | 2021-07-13 | Tuesday | 27920.19 |
## +----+------------+-----------------+---------------------+
## | 83 | 2021-07-14 | Wednesday | 28215.22 |
## +----+------------+-----------------+---------------------+
## | 84 | 2021-07-15 | Thursday | 28283.73 |
## +----+------------+-----------------+---------------------+
## | 85 | 2021-07-16 | Friday | 28140.02 |
## +----+------------+-----------------+---------------------+
## | 86 | 2021-07-17 | Saturday | 27869.78 |
## +----+------------+-----------------+---------------------+
## | 87 | 2021-07-18 | Sunday | 27535.27 |
## +----+------------+-----------------+---------------------+
## | 88 | 2021-07-19 | Monday | 27235.59 |
## +----+------------+-----------------+---------------------+
## | 89 | 2021-07-20 | Tuesday | 26972.28 |
## +----+------------+-----------------+---------------------+
## | 90 | 2021-07-21 | Wednesday | 26680.10 |
## +----+------------+-----------------+---------------------+
## | 91 | 2021-07-22 | Thursday | 26268.89 |
## +----+------------+-----------------+---------------------+
## | 92 | 2021-07-23 | Friday | 25670.04 |
## +----+------------+-----------------+---------------------+
## | 93 | 2021-07-24 | Saturday | 24874.49 |
## +----+------------+-----------------+---------------------+
## | 94 | 2021-07-25 | Sunday | 23989.51 |
## +----+------------+-----------------+---------------------+
## | 95 | 2021-07-26 | Monday | 23231.70 |
## +----+------------+-----------------+---------------------+
## | 96 | 2021-07-27 | Tuesday | 22679.94 |
## +----+------------+-----------------+---------------------+
## | 97 | 2021-07-28 | Wednesday | 22236.89 |
## +----+------------+-----------------+---------------------+
## | 98 | 2021-07-29 | Thursday | 21794.16 |
## +----+------------+-----------------+---------------------+
## | 99 | 2021-07-30 | Friday | 21345.45 |
## +----+------------+-----------------+---------------------+
plot(forecasting_NNAR,xlab = paste ("Time in", frequency ,y_lab , sep=" "), ylab=y_lab)
x1_test <- ts(testing_data, start =(rows-validation_data_days+1) )
lines(x1_test, col='red',lwd=2)
graph1<-autoplot(forecasting_NNAR,xlab = paste ("Time in", frequency ,y_lab , sep=" "), ylab=y_lab)
graph1
message("System finished Modelling and Forecasting by using BATS, TBATS, Holt's Linear Trend,ARIMA Model, and SIR Model ==>",y_lab, sep=" ")
## System finished Modelling and Forecasting by using BATS, TBATS, Holt's Linear Trend,ARIMA Model, and SIR Model ==>Forecast Third wave infection cases in Russia
message(" Thank you for using our System For Modelling and Forecasting ==> ",y_lab, sep=" ")
## Thank you for using our System For Modelling and Forecasting ==> Forecast Third wave infection cases in Russia