View source: R/variable_selection.R

Backward selection regression | R Documentation |

Backward selection regression.

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

`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". |

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.

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. |

Marios Dimitriadis

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

`fs.reg, univglms, cor.fsreg `

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

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