TLE-methods: TLE: robust mixture regression based on trimmed likelihood...
| TLE | R Documentation |
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)
