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"run.ci.examp" <-
function(reps=100,seed, method='z',n=25) {
if(!requireNamespace('tcltk', quietly = TRUE)){stop('The tcltk package is needed')}
if (!missing(seed)){ set.seed(seed) }
data <- matrix( rnorm( n*reps, 100, 10), ncol=n)
rmeans <- rowMeans(data)
ci.refresh <- function(...) {
conf.level=slider(no=1)
switch(method, Z=,z={
lower <- qnorm( (1-conf.level)/2, rmeans, 10/sqrt(n))
upper <- qnorm( 1-(1-conf.level)/2, rmeans, 10/sqrt(n))
},
T=,t= {
cv.l <- qt((1-conf.level)/2, n-1)
cv.u <- qt(1-(1-conf.level)/2, n-1)
rsds <- sqrt(apply(data,1,var))/sqrt(n)
lower <- rmeans+cv.l*rsds
upper <- rmeans+cv.u*rsds
},
BOTH=, Both=, both={
lz <- qnorm( (1-conf.level)/2, rmeans, 10/sqrt(n))
uz <- qnorm( 1-(1-conf.level)/2, rmeans, 10/sqrt(n))
cv.l <- qt((1-conf.level)/2, n-1)
cv.u <- qt(1-(1-conf.level)/2, n-1)
rsds <- sqrt(apply(data,1,var))/sqrt(n)
lt <- rmeans+cv.l*rsds
ut <- rmeans+cv.u*rsds
lower <- c(rbind(lt,lz,100))
upper <- c(rbind(ut,uz,100))
reps <- reps*3
rmeans <- rep(rmeans, each=3)
rmeans[c(F,F,T)] <- NA
},
stop("method must be z, t, or both") )
xr <- 100 + 4.5*c(-1,1)*10/sqrt(n)
plot(lower,seq(1,reps), type="n", xlim=xr, xlab="Confidence Interval",
ylab="Index")
abline( v= qnorm(c((1-conf.level)/2,1-(1-conf.level)/2), 100,
10/sqrt(n)), col='lightgreen')
if( method=="both" || method=="Both" || method=="BOTH"){
title( main="Confidence intervals based on both distributions",
sub="Upper interval is Z in each pair")
} else {
title( main=paste("Confidence intervals based on",method,"distribution"))
}
colr <- ifelse( lower > 100, 'blue', ifelse( upper < 100, 'red', 'black') )
abline(v=100)
segments(lower,1:reps,upper,1:reps, col=colr)
points( rmeans, seq(along=rmeans), pch='|', col=colr )
invisible(NULL)
}
slider( ci.refresh, 'Confidence Level', 0.5, 0.995, 0.005, 0.95,
title="Confidence Interval Demo")
}
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