# update_gamma: Updata Alpha and Sigma In EMSNM: EM Algorithm for Sigmoid Normal Model

## Description

Updata alpha and sigma in t+1 step with given data and coeffients estimated in step t.

## Usage

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

## Arguments

 `alphat` the estimated coeffients of the mean of each subgroup in step t `sigmat` the estimated standard error of Y in step t `etat` the estimated coeffients determining subgroup in step t `X` the covariables of the mean of each subgroup `Z` the covaraibles determining subgroup `Y` the respond variable

## Value

 `alpha` alpha estimated in step t+1. `eta` eta estimated in step t. `sigma` sigma estimated in step t+1.

Linsui Deng

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```#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) sigmatest <- 0.1 Wtest <- Wgenerate(alpha=alphatest,eta=etatest,X=Xtest,Z=Ztest) #test of updata_gamma thetaupdate_gamma <- update_gamma(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.