DIRMR (version 0.5.0)

ECME: ECME

Description

The ECME method calculates the conditional expectation of each hidden variable based on known data and current parameter estimates. Then, based on the known data, the conditional expectation of the hidden variables, and the current parameter estimates, the likelihood function is maximized to update the parameter estimates.

Usage

ECME(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)
ECME(data,df1,maxiter=15)