Seasonal AR: YtYt-s+et YtYt-s=(-1)(Yt-set Idea: Regress on estimate  YtYt-s (Yt-sto and get a t test. Distribution of t is far from standard normal. Modification: replace with deviations from Yt yt seasonal means. Visitors data: Estimate of 1-0.1556=0.8444 : Parameter Standard Variable DF Estimate Error t Value Pr>|t| Intercept 1 1099.20049 5.25 <.0001 Y_12 1 0.03191 -4.88 <.0001 XX Is t significant? What is the (null) distribution? Empirical (left) and N(0,1) (right) densities with means. Area to left of leftmost line (=-4.50, see next model) is 0.4061.
Seasonal AR: YtYt-s+et YtYt-s=(-1)(Yt-set Idea: Regress YtYt-s on (Yt-sto estimate  and get a t test. Distribution of t is far from standard normal. Modification: replace Yt with deviations yt from seasonal means. Visitors data: Estimate of : 1-0.1556=0.8444 Parameter Standard Variable DF Estimate Error t Value Pr>|t| Intercept 1 1099.20049 5.25 <.0001 Y_12 1 0.03191 -4.88 <.0001 XX Is t significant? What is the (null) distribution? Empirical (left) and N(0,1) (right) densities with means. Area to left of leftmost line (=-4.50, see next model) is 0.4061.
Dickey_Advenures%20in%20Forecasting%20Short%20Course.docx