boot: Parametric bootstrap

Description Usage Arguments Examples

Description

Parametric bootstrap for bivariate normally distributed data

Usage

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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

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# 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)

CAMAN documentation built on May 1, 2019, 9:21 p.m.

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