# Ccompute: Ccompute In EMSNM: EM Algorithm for Sigmoid Normal Model

## Description

Compute the probability of Y in given parameters alphat, sigmat, etat and variables X, Z by the Bayesian Formula under the assumption of Sigmoid-Normal Model.

## Usage

 `1` ```Ccompute(alphat, sigmat, etat, X, Z, Y) ```

## Arguments

 `alphat` the coeffients of the mean of each subgroup `sigmat` the variance of Y `etat` the coeffients determining subgroup `X` the covariables of the mean of each subgroup `Z` the covaraibles determining subgroup `Y` the respond variable

## Value

the probability of Y in given parameters alphat, sigmat, etat and variables X, Z under the assumption of Sigmoid-Normal Model.

Linsui Deng

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```#some variables samplesize <- 1000 classsize <- 6 etasize <- 3 alphasize <- 2 Xtest <- data.frame(matrix(rnorm(samplesize*etasize),samplesize,etasize)) Ztest <- matrix(rnorm(samplesize*alphasize),samplesize,alphasize) etatest <- matrix(seq(1.15,1,length=etasize*classsize),etasize,classsize) alphatest <- matrix(seq(1.15,1,length=alphasize*classsize),alphasize,classsize) Wtest <- Wgenerate(alpha=alphatest,eta=etatest,X=Xtest,Z=Ztest) #test of Ccompute sigmatest <- 1 Ctest <- Ccompute(alphat=alphatest,sigmat=sigmatest, etat=etatest,X=Wtest\$X,Z=Wtest\$Z,Y=Wtest\$Y) ```

EMSNM documentation built on May 2, 2019, 1:41 p.m.