CAMAN (version 0.78)

CAMANboot: Parametric bootstrap

Description

Parametric bootstrap for bivariate normally distributed data

Usage

CAMANboot(obs1, obs2, var1, var2, lambda11, lambda12, 
     prob1, lambda21, lambda22, prob2, rep, 
     data,numiter=10000,acc=1.e-7)

Arguments

obs1

the first column of the observations

obs2

the second column of the observations

data

a data frame

var1

Variance of the first column of the observations(except meta-analysis)

var2

Variance of the second column of the observations (except meta-analysis)

lambda11

first means of the first column of the observations

lambda12

first means of the second column of the observations

prob1

first mixing weight

lambda21

second means of the first column of the observations

lambda22

second means of the second column of the observations

prob2

second mixing weight

numiter

parameter to control the maximal number of iterations in the VEM and EM loops. Default is 5000.

acc

convergence criterion. Default is 1.e-7

rep

number of repetitions

Examples

# Parametric bootstrap for bivariate normally distributed data
data(CT)
library(mvtnorm)
hom1<-c(3.142442)
hom2<-c(-1.842393)
p1<-c(1)
start1<-c(2.961984,3.226141)
start2<-c(-2.578836, -1.500823)
pvem<-c(0.317,0.683)
CAMANboot(obs1=logitTPR, obs2=logitTNR, var1=varlogitTPR, var2=varlogitTNR,
          lambda11=hom1, lambda12=hom2, prob1=p1, 
          lambda21=start1, lambda22=start2, prob2=pvem,rep=3,data=CT)