This example uses the Raleigh Temps.jmp sample data table, which contains maximum monthly temperatures measured in degrees Fahrenheit from 1980 to 1990. Use the Time Series platform to examine the series and predict the maximum monthly temperatures for the next two years.
1.
Select Help > Sample Data Library and open Time Series/Raleigh Temps.jmp.
2.
Select Analyze > Specialized Modeling > Time Series.
3.
Select Temperature and click Y, Time Series.
4.
Select Month/Year and click X, Time ID.
5.
In the box next to Forecast Periods, type 24.
6.
Figure 15.2 Time Series Analysis Report for Raleigh Temps.jmp
8.
Set p, the autoregressive order, to 1 because the series showed evidence of autocorrelation.
9.
Click Estimate.
11.
In the ARIMA box, set p, the autoregressive order, to 1 because the series showed evidence of autocorrelation.
12.
In the Seasonal ARIMA box, set D, the seasonal differencing order, to 1 because the series showed evidence of seasonality.
13.
Click Estimate.
Figure 15.3 Model Comparison Table for Raleigh Temps.jmp

Help created on 7/12/2018