PRESS statistic from a regression using a power transformation

This macro computes the model fits, residuals, deleted fits, deleted prediction sum of squares (PRESS) residuals, and the PRESS statistic in the original units of the response when a power transformation of the response is applied in a linear regression.

This macro computes the model fits, residuals, deleted fits, deleted prediction sum of squares ((PRESS) residuals, and the PRESS statistic in the original units of the response when a power transformation of the response is applied in a linear regression.

Download the Macro

Be sure that Minitab knows where to find your downloaded macro. Choose File > Options > General. Under Macro location browse to the location where you save macro files.

Important

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Required Inputs

  • The number of predictors in the regression
  • The storage columns for the predictors
  • The storage column for the response
  • The power transformation parameters

Running the Macro

Suppose you have one predictor variable stored in C1, and the response variable is in C2. The transformation parameter value was -1.

  1. Choose View > Command Line/History and type the following:
    %PRESS
  2. Click Run. You will be prompted for additional information. For example:
    Please enter the number of predictor variables in the regression...
    DATA> 1
    Please enter column number of predictor variable...
    DATA> 1
    Please enter column number of response variable...
    DATA> 2
    Please enter response power transformation parameter value...
    DATA> -1 <-- reciprocal transformation of response specified
    

More Information

References

Allen, D. M. (1971), "The Prediction Sum of Squares as a Criterion for Selecting Predictor Variables," Technical Report Number 23, Department of Statistics, University of Kentucky.

Delozier, M. R. (2004), Introduction to Applied Industrial Statistics, Industrial Short-Course Participant Manual.

Myers, R. H. (1990), Classical and Modern Regression