simulateLogit: A function to generate random data from a logit model.

In BPJandree/AutoGLM: Automated fitting, model selection, and documentation functions for GLM modelling of binary response variables.

Description

This function generates random data simulated from a logit model based on the parameters supplied.

Usage

simulateLogit(nobs = 2500, pars = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0))

Arguments

nobs	number of observations that the returned dataset should include. Defaults to 2500.
pars	A vector of parameters to be used in the data generating process. Regressors may have a 0 coefficient. Defaults to 0 for all variables.

Value

A simulated dataset from a logistic probability model with nobs observations, a binary response variable, and nxregs regressors ranging from 0 to 100.

Examples

logitpars <- c(-0.5, 0.4, -0.3, 0.2, -0.1, 0, 0, 0, 0, 0, 0, 0)
logit_data <- simulateLogit(nobs=2500, pars=logitpars)

random_binaryResponse_data <- simulateLogit(nobs=500)

BPJandree/AutoGLM documentation built on May 5, 2019, 10:25 a.m.