Hello,
I understand that you are trying to remove terms with high p-values from a stepwise regression model of your data. In order to do this, I would recommend setting the ‘ PRemove ’ property of the stepwiselm function.
Let me explain this further using your code. The first line of your code:
stepwiselm(X, ‘linear’, ‘PEnter’, 0.05)
is building a regression model of your X data. Initially, it only includes ‘ linear ’ terms of the regression model. Then, the ‘ PEnter ’ property allows additional terms to be included in the regression model only if their p-value is less than 0.05. Note however, in the above line of code, the ‘ PRemove ’ property is already set by default to 0.10. This means that only terms with p-values greater than 0.10 are actually removed from the regression model. Please refer to the following documentation link for more information about the ‘ PRemove ’ property:
In order to exclude regression terms with a p-value of greater than 0.05, your first line of code should be modified to:
stepwiselm(X, ‘linear’, ‘PEnter’, 0.025, ‘PRemove’, 0.05)
This should remove any regression terms with a p-value greater than 0.05.
As you mentioned in your question, setting the ‘ Upper ’ property of the stepwiselm function constrains the regression model to use only ‘ linear ’ terms. Yes, it probably is only a coincidence here that the p-values of the regression terms with this setting are all less than 0.05.
The MATLAB documentation contains some detailed examples that can help clarify the use of stepwiselm:
