Discussion-Week-7-Notes.R

library(tidyverse)

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library(mosaic)

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library(ggformula)
library(readr)
library(fpp2)

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##DISCUSSION WEEK 7
## READ IN US GAS DATA
usgas <- read_csv("E:/WOODS/ADECXXXX/usgas.csv")

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##   GasBarrelsK = col_double()
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gas <- usgas$GasBarrelsK
gasts <- ts(gas, start = c(1945, 1), frequency = 12)
autoplot(gasts)

## Create Train and Test Data Sets
## Create Test and Training Sets - split out 2018 onward, about 30 months
train <- window(gasts, start = 1945, end=c(2016,12))
test <- window(gasts, start =c(2017,1))

# Fit Neural Net Model
netmod <- nnetar(train, lambda = 0)
fcnetmod <- forecast(netmod,h=60)
autoplot(fcnetmod) + ylab("Gas Barrels - 1000") + xlab("Monthly Demand") + theme_bw()

netmod2 <- nnetar(train, lambda = 1)
fcnetmod2 <- forecast(netmod2,h=60)
autoplot(fcnetmod2) + ylab("Gas Barrels - 1000") + xlab("Monthly Demand") + theme_bw()

fcnetmod2PI <- forecast(netmod2,PI=TRUE, h=60)
autoplot(fcnetmod2PI) + ylab("Gas Barrels - 1000") + xlab("Monthly Demand") + theme_bw()