Develop two forecast models for the AmTrk ridership data $($as shown on next slide$)$: first

the linear model A$,$ then the non$-$linear model B with addition of the seasonality terms.

Model A: $0+$t

Model B: $0+1*$t $+2*$sin$(2*$pi$*$t$/12)+3*$cos$(2*$pi$*$t$/12)$

Plot AmTrk ridership data vs$.$ time for the first $48$ month with appropriate x$-$y coordinate

labeling. Graphically assess the long$-$term trend from the raw data. Build the multiple

regression model A x $=$ b for Model A and Model B respectively based on the first $48$ month

data. Compute $\{0,\}$ and $\{0,1,2,3\}$ using Matlab function A$\backslash$b$.$

With the preceding forecast models predict the ridership for the next $6$ month beyond

$48$th month since Jan $1991.$ Compare with the actual, calculate the monthly forecast errors,

and estimate the RMS $($Root Mean Square$)$ errors for a$)$ three$-$month forecast, and b$)$ six$-$month

forecast. What is your evaluation of the comparative forecast performance of Model A versus

Model B based on the RMS errors?