ParEst: Estimate theta and psi in multinomial mixture model

Description Usage Arguments Value Examples

View source: R/ParEst.R

Description

This function is used to estimate theta and psi in multinomial mixture model given the number of components k.

Usage

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ParEst(data, d, k, TT = 1000)

Arguments

data

- data in matrix formation with n rows and p columns

d

- number of categories for each variable

k

- number of components

TT

- number of iterations in Gibbs sampler, default value is 1000. T should be an even number for 'burn-in'.

Value

theta - vector of probability for each component

psi - specific probability for each variable in each component

Examples

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# dimension parameters
n<-200; p<-5; d<-rep(2,p);
# generate complete data
Complete<-GenerateData(n, p, d, k = 3)
# mask percentage of data at MCAR
Incomplete<-Complete
Incomplete[sample(1:n*p,0.2*n*p,replace = FALSE)]<-NA
# k identify
K<-kIdentifier(data = Incomplete, d, TT = 10)
Par<-ParEst(data = Incomplete, d, k = K$k_est, TT = 10)

MMDai documentation built on Dec. 7, 2017, 5:05 p.m.