kIdentifier: Identify the suitable number of components k

In MMDai: Multivariate Multinomial Distribution Approximation and Imputation for Incomplete Categorical Data

Description

This function is used to find the suitable number of components k.

Usage

kIdentifier(data, d, TT = 1000, alpha = 0.25)

Arguments

data	- data in matrix formation with n rows and p columns
d	- number of categories for each variable
TT	- number of iterations in Gibbs sampler, default value is 1000. T should be an even number for 'burn-in'.
alpha	- hyperparameter that could be regarded as the pseudo-count of the number of samples in the new component

Value

k_est - posterior estimation of k

k_track - track of k in the iteration process

Examples

# 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)

MMDai documentation built on May 2, 2020, 9:05 a.m.