Description Usage Arguments Value Author(s) See Also Examples
Stepwise DMR is a backward model selection procedure which simultaneously deletes continuous variables and merges levels of factors. It is a stepwise version of DMR, where in every step the values of squared t-statistics are recalculated. The final model is selected by minimization of generalized information criterion in the nested family of models.
1 |
model |
initial model of class lm. |
K |
penalty for the number of parameters in generalized information criterion, default is log(n). |
a list including elements
Partitions |
a list of partitions of factors for the models on the nested path searched through |
Crit |
values of generalized information criterion for the models on the nested path searched through |
LogLik |
values of log-likelihood for the models on the nested path searched through |
Best |
a list containing features of the selected model: Partition, Model of class lm, Crit and Hypotheses represesnted as a matrix of lienear hypotheses imposed on the model's parameters |
Piotr Pokarowski, Agnieszka Prochenka, Aleksandra Maj
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