samplemixNoise: Generate data from a mixture of normals with additionally...

In ococrook/sugsvarsel: SUGS algorithm of Wang and Dunson (2011), SUGS VarSel algorithm Crook et al.

Description

Generate data from a mixture of normals with additionally noisy variables

Usage

samplemixNoise(N, weights, mean, cov, p, meanNoise, covNoise, struc = "Diag")

Arguments

N	The number of observations to be generated
weights	A vector of weights for each mixture component
mean	A list containing the means for each component
cov	A list containing covariance matrix or variance vectors. See paramater struc
p	The number of noisy variables
meanNoise	A vector of the means of each of the noisy variables
covNoise	A vector of standard deviations
struc	A character string indicating the structure of the covariance matrix. Diagonal is selected by default and cov should be provided as a list of vectors. If "Full" is specified, then cov should be provided as list of covariance matricies.

Value

A list of three of length three. The first the mixture weights, the second a data matrix containing the observations, and the third a vector of the componenet allocations.

ococrook/sugsvarsel documentation built on May 27, 2019, 12:12 p.m.