mixtools (version 1.0.1)

lambda: Local Estimation for Lambda in Mixtures of Regressions

Description

Return local estimates of the mixing proportions from each component of a mixture of regressions model using output from an EM algorithm.

Usage

lambda(z, x, xi, h = NULL, kernel = c("Gaussian", "Beta", 
       "Triangle", "Cosinus", "Optcosinus"), g = 0)

Arguments

z

An nxk matrix of posterior probabilities obtained from the EM algorithm.

x

A vector of values for which the local estimation is calculated.

xi

An nx(p-1) matrix of the predictor values.

h

The bandwidth controlling the size of the window used for the local estimation.

kernel

The type of kernel to be used for the local estimation.

g

A shape parameter required for the symmetric beta kernel. The default is g = 0 which yields the uniform kernel. Some common values are g = 1 for the Epanechnikov kernel, g = 2 for the biweight kernel, and

Value

• lambda returns local estimates of the mixing proportions for the inputted x vector.

See Also

regmixEM.loc