View source: R/regression_models.R
Multinomial regression | R Documentation |
Multinomial regression.
multinom.reg(y, x, tol = 1e-07, maxiters = 100)
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. |
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. |
Michail Tsagris and Stefanos Fafalios.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Stefanos Fafalios stefanosfafalios@gmail.com.
Bohning, D. (1992). Multinomial logistic regression algorithm. Annals of the Institute of Statistical Mathematics, 44(1): 197-200.
logiquant.regs, fbed.reg
y <- iris[, 5]
x <- matrix( rnorm(150 * 2), ncol = 2 )
mod <- multinom.reg(y, x)
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