R: Multinomial regression

Multinomial regression {Rfast} | R Documentation

## Multinomial regression

### Description

Multinomial regression.

### Usage

    multinom.reg(y, x, tol = 1e-07, maxiters = 50)

### Arguments

`y` | The response variable. A numerical or a factor type vector.
`x` | A matrix or a data.frame with the predictor variables.
`tol` | This tolerance value to terminate the Newton-Raphson algorithm.
`maxiters` | The maximum number of iterations Newton-Raphson will perform.

### Value

A list including:

`iters` | The number of iterations required by the Newton-Raphson.
`loglik` | The value of the maximised log-likelihood.
`be` | A matrix with the estimated regression coefficients.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>.

### References

Bohning, D. (1992). Multinomial logistic regression algorithm. Annals of the Institute of Statistical Mathematics, 44(1): 197-200.

### See Also

`glm_logistic, score.multinomregs logistic_only`

### Examples

    ## Not run:
    y <- iris[, 5]
    x <- matrnorm(150, 3)
    res <- multinom.reg(y, x)

    ## End(Not run)

[Package Rfast version 2.0.0 Index]