graphics.off();           # shuts down all the open graphics plots
objects();                # prints a list of all variables in memory
remove(list=objects());   # sets objects() as a list, and then removes this list
                          # of variables from memory
options(scipen=20);       # sets the decimal places in scientific notation

library(stats);
# loads the "stats" package, which contains the arima() routine.

sink(file = "arma.out", append = FALSE, type = "output", split = TRUE);
# creates a disk file of the terminal/screen output; type can be changed to
# log inputted commands as well.

myData <- read.table("data2.txt", header=TRUE);
X1     <- as.matrix(myData$y);
# loads a disk file of data series.  the series should be in columns and include
# a header.
n=nrow(myData);

myArma <- arima(X1, order = c(1,0,1), method=c("ML"));
# runs a "canned" arima regression with p=1 and q=1, where d is the level
# of differencing.


print(myArma);

print("ARMA Coefficients:");
print( coef(myArma)[1] ); 
print( coef(myArma)[2] );
print("Coefficient standard deviations:");
print( sqrt( vcov(myArma)[1,1] ) );
print( sqrt( vcov(myArma)[2,2] ) );
print("AIC");
print(myArma$aic);
# prints out the estimates of the AR and MA coefficient mean and standard
# deviations.
print("Estimate of the innovations variance:");
print(myArma$sigma2);
# prints out estimate of the mean of the ARMA residuals (innovations) variance.

print("Coefficient t-stats:");
print( coef(myArma)[1] / sqrt(vcov(myArma)[1,1]) );
print( coef(myArma)[2] / sqrt(vcov(myArma)[2,2]) );
# prints out t-statistics.

acf(myArma$residuals, 100);
# shows an acf plot of the ARMA residuals out to 100 lags.

print(Box.test(myArma$residuals, n/4, type = "Ljung-Box"));
# runs a Ljung-box test on the ARMA residuals.

print("Predicted values for time-series:");
print(predict(myArma, n.ahead=100, se.fit=TRUE));
# Calculate 10 step ahead forecasts for the level of the
# series, and provide standard errors of prediction.

forecast <- predict(myArma, n.ahead=100, se.fit=TRUE);

plot.ts( forecast$pred );

sink(file = NULL);
# closes the opened disk file opened above with sink.