mixreg {MixSemiRob}

MLE of Mixture Regression with Normal Errors

Description

‘mixreg’ provides the MLE estimates of a mixture of regression models with normal errors. The result from this function can be used as initial values of the mixregRM2 function.

Usage

mixreg(x, y, C = 2, nstart = 20, tol = 1e-05)

Arguments

x

an n by p data matrix where n is the number of observations and p is the number of explanatory variables. The intercept term will automatically be added to the data.

y

an n-dimensional vector of response variable.

C

number of mixture components. Default is 2.

nstart

number of initializations to try. Default is 20.

tol

stopping criteria (threshold value) for the EM algorithm. Default is 1e-05.

Value

A list containing the following elements:

pi

C-dimensional vector of estimated mixing proportions.

beta

C by (p + 1) matrix of estimated regression coefficients.

sigma

C-dimensional vector of estimated standard deviations.

lik

final likelihood.

run

total number of iterations after convergence.

See Also

mixregRM2

Examples

data(tone)
y = tone$tuned
x = tone$stretchratio
k = 160
x[151:k] = 0
y[151:k] = 5
est = mixreg(x, y, 2, nstart = 1)