And you can compare their results to see how close the simulated data is to your original data. The simulated data table has three scripts. Your original data table has three scripts. Then as the row number increases, the formula calculates new values recursively based upon the value from the previous row. So the formula says, if it is the first row, just simulate some number according to the sample, here looks like a random Normal(0,1) fits the bill. First imagine how a JMP table evaluate the formula, it is row by row.
And see how they are used in the formula. You need three numbers from the previous report: two parameter estimates, and standard deviation in Model Summary.
Next, create a formula column like the following. I include the script in your original data and attach the updated data table. It is a type of time series model which describe a process with auto-correlation.įor AR(1) model, simulating it by using JMP formula column can be done by the following steps:įirst, fit the AR(1) model and here is the report: It looks like your data can be adequately modeled by a so called AR(1) model, short for A utoregressive of Order One.
