Entering values for estimated model parameters

There are several scenarios for which you might enter values for estimated model parameters when using a regression with life data, probit analysis, or accelerated life testing For example, you may want to provide starting estimates so that the algorithm used to calculate the parameters converges to a solution. You can also enter model parameters to cross-validate a model with an independent sample.

  • Convergence: The maximum likelihood solution may not converge if the starting estimates are not in the neighborhood of the true solution. If the algorithm does not converge to a solution, you can specify what you think are good starting values for parameter estimates in Use starting estimates in the Options subdialog box.
  • Validation: You may also want to validate the model with an independent sample. To do this, split the data into two subsets. Use the first subset of data to estimate and store the coefficients. If you enter these estimates in Use historical estimates in the Options subdialog box. Minitab uses these values as the parameter estimates rather than calculating new parameter estimates. Then, you can assess the model fit for the independent sample.

In all cases, enter a column with entries that correspond to the model terms in the order you entered them in the Model box. With complicated models, find out the order of entries for the starting estimates column by looking at the regression table in the output.

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