Estimating the model parameters
main topic  

Minitab uses a modified Newton-Raphson algorithm to estimate the model parameters. If you like, you can enter your own parameters. In this case, no estimation is done; all results - such as the percentiles - are based on these parameters.

When you let Minitab estimate the parameters from the data, you can optionally:

·    enter starting values for the algorithm.

·    change the maximum number of iterations for reaching convergence (the default is 20). Minitab obtains maximum likelihood estimates through an iterative process. If the maximum number of iterations is reached before convergence, the command terminates.

·    estimate other model coefficients while holding the shape parameter (Weibull) or the scale parameter (other distributions) fixed at a specific value.

Why enter starting values for the algorithm? The maximum likelihood solution may not converge if the starting estimates are not in the neighborhood of the true solution, so you may want to specify what you think are good starting values for parameter estimates.

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.