# boot: Parametric bootstrap In CAMAN: Finite Mixture Models and Meta-Analysis Tools - Based on C.A.MAN

 CAMANboot R Documentation

## 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)
``````

CAMAN documentation built on April 11, 2023, 6:08 p.m.