Multinomial regression {Rfast2}

Multinomial regression

Description

Multinomial regression.

Usage

multinom.reg(y, x, tol = 1e-07, maxiters = 100)

Arguments

y

The response variable. A numerical or a factor type vector.

x

A matrix or a data.frame with the predictor variables.

tol

The 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 and Stefanos Fafalios.

R implementation and documentation: Michail Tsagris [e-mail] and Stefanos Fafalios [e-mail].

References

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

See Also

logiquant.regs, fbed.reg

Examples

y <- iris[, 5]
x <- matrix( rnorm(150 * 2), ncol = 2 )
mod <- multinom.reg(y, x)