bestlm {nsRFA} | R Documentation

## Subsets regression

### Description

`bestlm` performs an exhaustive search for the best subsets of the variables in `ind` for predicting `dip` in linear regression.

### Usage

     bestlm (dip, ind, kmax=4, nbest=3)
     ## S3 method for class 'bestlm':
     print (x, ...)
     ## S3 method for class 'bestlm':
     summary (object, ...)

### Arguments

`x` | object of class `bestlm`, output of function `bestlm`
`object` | object of class `bestlm`, output of function `bestlm`
`dip` | vector n x 1 of dependent variable to be predicted
`ind` | matrix n x K of the K independent variables (candidate predictors)
`kmax` | maximum size (number of regressors) to report
`nbest` | number of subsets of each size to report
`...` | other arguments

### Details

This function has been obtained using the function `leaps` of the R package `leaps`. It is based on the Alan Miller's FORTRAN routines.

Warning: the function will stop with an error if `ind` is not of full rank or if it has more than 31 columns.

### Value

`bestlm` returns the following values:
`subselect` matrix (kmax*nbest)x(ncol(ind)) with the sets of chosen linear models, ordered in function of the adjusted coefficient of determination (R2adj);
`R2adj` the ordered adjusted coefficient of determination;

### Note

For information on the package and the Author, and for all the references, see `nsRFA`.

### See Also

`lm`, `REGRDIAGNOSTICS`.

### Examples

    data(hydroSIMN)

    bestlm(parameters[,"Dm"], parameters[,-c(1:2)])

    regr <- lm(Dm ~ Am + S2000 + NORD, parameters); regr
    summary(regr)

[Package nsRFA version 0.6-9 Index]