R: Backward selection regression

Backward selection regression {Rfast} | R Documentation

## Backward selection regression

### Description

Backward selection regression.

### Usage

    bs.reg(y, x, alpha = 0.05, type = "logistic")

### Arguments

`y` | A numerical vector with the response variable values. It can either be of 0 and 1 values (Logistic regression) or of integer values 0, 1, 2,... (Poisson regression).
`x` | A numerical matrix with the candidate variables.
`alpha` | Threshold (suitable values are in [0,1]) for assessing the significance of p-values. The default value is at 0.05.
`type` | For the Logistic regression put "logistic" (default value) and for Poisson type "poisson".

### Details

This function currently implements only the binary Logistic and Poisson regressions. If the sample size is less than the number of variables a notification message will appear and no backward regression will be performed.

### Value

The output of the algorithm is an S3 object including:

`info` | A matrix with the non selected variables and their latest test statistics and p-values.
`Vars` | A vector with the selected variables.

### Author(s)

Marios Dimitriadis

R implementation and documentation: Marios Dimitriadis <mtsagris@csd.uoc.gr>

### See Also

`fs.reg, univglms, cor.fsreg`

### Examples

    y <- rbinom(50, 1, 0.5)
    x <- matrnorm(50, 10)
    res<-bs.reg(y, x)

[Package Rfast version 2.0.4 Index]