Use R studio to answer ARMA questions

# Make the required packages available to use.

#————————————————————————————-

library(xts)

library(forecast)

library(TSSS)

#————————————————————————————-

# Load the right data, using the dataset number emailed to you (301 is not right for you).

#————————————————————————————-

data <- readRDS(file = “lecture 09 assignment data 301.rds”)

N <- nrow(data)

if (!exists(“data”)) { # only worry about this warning if it is red.

 message(“There was a problem loading your data.”)

 message(“Make sure the ‘.rds’ files are in the directory containing this script and make sure that directory is your working directory.”)

 message(“If that does not work, get help.”)

}

if (N < 100 || ncol(data) != 5) { # only worry about this warning if it is red.

 message(“Make sure that the data variable contains 5 data series, each with more than 100 observations.”)

}

#——————————————————————————————

# Series 1 analysis example – adapt this to reflect your own data.

#——————————————————————————————

x <- data$series1

# Identifying ARMA(P,Q) model

par(mfrow=c(3,1))

plot.ts(x, main=”Plot against time”)

acf (x, lag = 20, main=”Autocorrelation plot”)

pacf (x, lag = 20, main=”Partial autocorrelation plot”)

par(mfrow=c(1,1))

# Set the order of the ARIMA model to c(P,0,Q) to estimate a ARMA(P,Q) model.

summary(fit <- Arima(x, order=c(0,0,0), include.mean = TRUE ))

fit$code

acf(fit$residuals)

#——————————————————————————————

# Series 2 analysis – add your own code here

#——————————————————————————————

x <- data$series2

# Identifying ARMA(P,Q) model

par(mfrow=c(3,1))

plot.ts(x, main=”Plot against time”)

acf (x, lag = 20, main=”Autocorrelation plot”)

pacf (x, lag = 20, main=”Partial autocorrelation plot”)

par(mfrow=c(1,1))

#——————————————————————————————

# Series 3 analysis – add your own code here

#——————————————————————————————

x <- data$series3

# Identifying ARMA(P,Q) model

par(mfrow=c(3,1))

plot.ts(x, main=”Plot against time”)

acf (x, lag = 20, main=”Autocorrelation plot”)

pacf (x, lag = 20, main=”Partial autocorrelation plot”)

par(mfrow=c(1,1))

#——————————————————————————————

# Series 4 analysis – add your own code here

#——————————————————————————————

x <- data$series4

# Identifying ARMA(P,Q) model

par(mfrow=c(3,1))

plot.ts(x, main=”Plot against time”)

acf (x, lag = 20, main=”Autocorrelation plot”)

pacf (x, lag = 20, main=”Partial autocorrelation plot”)

par(mfrow=c(1,1))

#——————————————————————————————

# Series 5 analysis – add your own code here

#——————————————————————————————

x <- data$series5

# Identifying ARMA(P,Q) model

par(mfrow=c(3,1))

plot.ts(x, main=”Plot against time”)

acf (x, lag = 20, main=”Autocorrelation plot”)

pacf (x, lag = 20, main=”Partial autocorrelation plot”)

par(mfrow=c(1,1))

Answer these questions:

Question 12 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 1 has P equal to:

Question 22 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 1 has Q equal to:

Question 32 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 2 has P equal to:

Question 42 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 2 has Q equal to:

Question 52 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 3 has P equal to:

Question 62 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 3 has Q equal to:

Question 72 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 4 has P equal to:

Question 82 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 4 has Q equal to:

Question 92 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 5 has P equal to:

Question 102 pts

The ARMA(P,Q) model that best describes the autocorrelation structure of series 5 has Q equal to:

hey, here is the R studio, access from here : https://drive.google.com/file/d/1Gx5HQSHrC0F10mHhd…

this is the data file: https://drive.google.com/file/d/1VdT2EtbbAycN3zrm9…