DIRMR (version 0.5.0)

MCEM: MCEM

Description

The MCEM method is an algorithm that utilizes the Monte Carlo method to solve the difficult E-step integral in the EM algorithm. It avoids complex numerical integration calculations by converting the integral in the E-step into a numerical integral.

Usage

MCEM(data, df1, maxiter)

Value

Y01

The response variable value after projection

Yhat

The estimated response variable value after projection

Arguments

data

The real data sets with missing data used in the method

df1

The real data sets used in the method

maxiter

The maximum number of iterations

Author

Guangbao Guo,Yu Li

Examples

set.seed(99)
library(MASS)
library(mvtnorm)
n=50;p=6;q=5;M=2;omega=0.15;ratio=0.1;maxiter=15;nob=round(n-(n*ratio))
dd.start=1;sigma2_e.start=1
X0=matrix(runif(n*p,0,2),ncol=p)
beta=matrix(rnorm(p*1,0,3),nrow=p)
Z0=matrix(runif(n*q,2,3),ncol=q)
e=matrix(rnorm(n*1,0,sigma2_e.start),n,1)
b=matrix(rnorm(q*1,0,1),q,1)
Y0=X0
df1=data.frame(Y=Y0,X=X0,Z=Z0)
misra=function(data,ratio){
  nob=round(n-(n*ratio))
  data[sample(n,n-nob),1]=NA
  return(data)}
data=misra(data=df1,ratio=0.1)
MCEM(data,df1,maxiter=15)