topic Re: ARIMA Time Series by ACF, PACF in Discussions https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12997#M12295 <HTML><HEAD></HEAD><BODY><P>Generally I look at these plots to see which lag(s) have the highest correlation coefficients to help determine differencing order for the AR component and seasonal interval if I'm contemplating some sort of seasonal ARIMA model. I also try to use some process knowledge to validate, in a non-statistical sense, my differencing and seasonal interval guesses. For example...if I were monitoring temperature in my home, controlled by a thermostat, on a minute by minute basis, I'd suspect a differencing order close to 1 to be the best. If I were monitoring my home's monthly natural gas consumption, I'm guessing that a seasonal lag component would be 12 months out in time. Seriesg.jmp in the JMP Sample Data Directory is a good sample data set to illustrate these concepts.</P></BODY></HTML> Tue, 30 Jun 2015 17:53:08 GMT Peter_Bartell 2015-06-30T17:53:08Z ARIMA Time Series by ACF, PACF https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12996#M12294 <HTML><HEAD></HEAD><BODY><P>How do you use the time series ACF and PACF plots to suggest the nonseasonal and seasonal AR components of the ARIMA model?</P></BODY></HTML> Mon, 29 Jun 2015 19:17:59 GMT https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12996#M12294 meredith_a_habl 2015-06-29T19:17:59Z Re: ARIMA Time Series by ACF, PACF https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12997#M12295 <HTML><HEAD></HEAD><BODY><P>Generally I look at these plots to see which lag(s) have the highest correlation coefficients to help determine differencing order for the AR component and seasonal interval if I'm contemplating some sort of seasonal ARIMA model. I also try to use some process knowledge to validate, in a non-statistical sense, my differencing and seasonal interval guesses. For example...if I were monitoring temperature in my home, controlled by a thermostat, on a minute by minute basis, I'd suspect a differencing order close to 1 to be the best. If I were monitoring my home's monthly natural gas consumption, I'm guessing that a seasonal lag component would be 12 months out in time. Seriesg.jmp in the JMP Sample Data Directory is a good sample data set to illustrate these concepts.</P></BODY></HTML> Tue, 30 Jun 2015 17:53:08 GMT https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12997#M12295 Peter_Bartell 2015-06-30T17:53:08Z Re: ARIMA Time Series by ACF, PACF https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12998#M12296 <HTML><HEAD></HEAD><BODY><P>Ok, thx. This works.</P></BODY></HTML> Tue, 30 Jun 2015 19:10:48 GMT https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12998#M12296 meredith_a_habl 2015-06-30T19:10:48Z Re: ARIMA Time Series by ACF, PACF https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12999#M12297 <HTML><HEAD></HEAD><BODY><P>Glad to help!</P></BODY></HTML> Tue, 30 Jun 2015 19:17:58 GMT https://community.jmp.com/t5/Discussions/ARIMA-Time-Series-by-ACF-PACF/m-p/12999#M12297 Peter_Bartell 2015-06-30T19:17:58Z