opt.t: Optimization routine based on step-wise elimenation using...

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

Description

This function searches

Usage

opt.t(model, Y, X, returntype = "model", tracelevel = 0, crit.t = 1.64,
  memorymanagement = FALSE)

Arguments

model	The model to be optimized. Supports "lm" for the linear probability model, "logit" for the logistic probability model, and "probit" for the probit model.
Y	The binary response variable.
X	A dataframe with collumns of exogenous regressors.
returntype	"model", "data", or "colnames"
tracelevel	level of printing.
crit.t	t-value used for significance test.
memorymanagement	logical, indicating whether memory should be more actively managed.

Value

"model", "data", or "colnames", to be specified in returnype.

Examples

randomlogit <- simulateLogit(nobs=500, pars = c(0.5, -0.4, -0.3, 0.1, 0.05, 0.025, 0, 0, 0, 0))
Y=randomlogit[,1]
X=randomlogit[,-1]
opt.t(model="lm", Y, X)

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