CAMANboot {CAMAN} | R Documentation |
Parametric bootstrap for bivariate normally distributed data
CAMANboot(obs1, obs2, var1, var2, lambda11, lambda12, prob1, lambda21, lambda22, prob2, rep, data,numiter=10000,acc=1.e-7)
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 |
# 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)