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# PDunnett is a secondary function which computes the cumulative
# distribution function of the Dunnett distribution in one-sided
# hypothesis testing problems with a balanced one-way layout and
# equally weighted null hypotheses
#library(mvtnorm)
pdunnett<-function(x,df,m)
# X, Argument
# DF, Number of degrees of freedom
# M, Number of comparisons
{
# Correlation matrix
corr<-matrix(0.5,m,m)
for (i in 1:m) corr[i,i]<-1
p<-pmvt(lower=rep(-Inf,m), upper=rep(x,m), delta=rep(0,m), df=df, corr=corr, algorithm=GenzBretz(maxpts=25000, abseps=0.00001, releps=0))[1]
return(p)
}
# End of pdunnett
# QDunnett is a secondary function which computes a quantile of the
# Dunnett distribution in one-sided hypothesis testing problems
# with a balanced one-way layout and equally weighted null hypotheses
#library(mvtnorm)
qdunnett<-function(x,df,m)
# X, Argument
# DF, Number of degrees of freedom
# M, Number of comparisons
{
# Correlation matrix
corr<-matrix(0.5,m,m)
for (i in 1:m) corr[i,i]<-1
temp<-qmvt(x,interval=c(0,4),tail="lower.tail",df=df, delta=rep(0,m),corr=corr, algorithm=GenzBretz(maxpts=25000, abseps=0.00001, releps=0))[1]
return(temp$quantile)
}
# End of qdunnett
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