During an era, i.e, a block of time, the rules seem fairly constant. Between eras, the rules may change. This was an issue when considering modeling a disease over time; the rules might change when an effective treatment is released. Less critically, could I empirically replicate the era's in baseball. A paper at the Discovery Summit suggested using GenReg (https://community.jmp.com/docs/DOC-7736). A dataset,modernera.jmp, is attached.
It requires creating many dummy variables. For each year, create a column with a formula "less than that year". The formula for a column "1926" is shown. The fist tab In the script automates this.The column "yearID" contained the time series. Check the box to start GenReg, this can easily be achieved with the existing options in "Fit Model". RPG is the Y since we are interested in change points in runs per game. Saving the prediction formula shows all the information you need for change points. However, I wanted to create labels for the empirical periods, which is the reason for the second tab created by running the script.