blm_choice: Choice of Best Linear Model
In jmcimula/cblmr: The Choice of the Best Linear Model

This function allows you to choose the best model from among different "best" models. Evaluating based on predictions and goodness of fit.

1	blm_choice(dataframe, response, exp.comb, ..., choice = FALSE)

`dataframe`	only numerical values are required(explanatory and response variables)
`response`	dependent variable
`exp.comb`	number of expected combinations
`choice`	when choice=TRUE it return the best model based on exp.comb. Default choice=FALSE

Evaluating based on predictions(PRESS : Prediction Sum of Squares) and goodness of fit(AIC, BIC, R Squared, Adj. Squared).

a tab grouping predictions and goodness of fit per model

Jean Marie Cimula

jmcimula/cblmr documentation built on May 19, 2019, 1:52 p.m.

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