TLE-methods: TLE: robust mixture regression based on trimmed likelihood...

In changwn/RMR: Robust Mixture Regression

TLE: robust mixture regression based on trimmed likelihood estimation.

Description

The algorithm fits a mixture regression model after trimming a proportion of the observations, given by tRatio.

Usage

TLE(formula, data, nc = 2, tRatio, MaxIt = 200)

## S4 method for signature 'formula,ANY,numeric,numeric,numeric'
TLE(formula, data, nc = 2, tRatio, MaxIt = 200)

Arguments

formula	A symbolic description of the model to be fit.
data	A data frame containing the predictor and response variables, where the last column is the response varible.
nc	Number of mixture components.
tRatio	Trimming proportion.
MaxIt	Maximum iteration.

Value

A S4 object of RobMixReg class.

Examples

library("RobMixReg")
formula01=as.formula("y~x")
x=(gaussData$x);y=as.numeric(gaussData$y);
example_data01=data.frame(x,y)

res = TLE(formula01,example_data01, nc=2,tRatio=0.05,MaxIt=200)

changwn/RMR documentation built on March 29, 2025, 3:15 p.m.