clogitboost {clogitboost} R Documentation

## Boosting conditional logit model

### Description

Fit a boosting conditional logit model using componentwise smoothing spline.

### Usage

clogitboost(y, x, strata, iter, rho)


### Arguments

 y vector of binary outcomes. x matrix or data frame with each column being a covariate. strata vector of group membership, i.e., items in the same group have the same value. iter number of iterations. rho learning rate parameter in the boosting algorithm.

### Value

The function clogitboost returns the following list of values:

 call original function call. func list of fitted spline functions. index list of indices indicating which covariate is used as input for the smoothing spline. theta list of fitted coefficients in the conditional logit models. loglike sequence of fitted values of log-likelihood. infscore relative influence score for each covariate. rho learning rate parameter, which typically takes a value of 0.05 or 0.1. xmax maximal element of each covariate. xmin minimal element of each covariate.

### Author(s)

Haolun Shi shl2003@connect.hku.hk

Guosheng Yin gyin@hku.hk

plot.clogitboost

predict.clogitboost

### Examples

data(travel)
train <- 1:504
y <- travel$MODE[train] x <- travel[train, 3:6] strata <- travel$Group[train]
fit <- clogitboost(y = y, x = x, strata = strata, iter = 10, rho = 0.05)


[Package clogitboost version 1.1 Index]