
dtikuv(x, d, mean=0, sigma=1)
ptikuv(q, d, mean=0, sigma=1)
qtikuv(p, d, mean=0, sigma=1, ...)
rtikuv(n, d, mean=0, sigma=1, Smallno=1.0e-6)
tikuv
for more details.
For rtikuv
, arguments mean
and sigma
must be of
length 1.ptikuv(L) < Smallno
and ptikuv(U) > 1-Smallno
where L
and U
are the loweuniroot
.dtikuv
gives the density,
ptikuv
gives the cumulative distribution function,
qtikuv
gives the quantile function, and
rtikuv
generates random deviates.tikuv
for more details.tikuv
.x = seq(-5, 5, len=401)
plot(x, dnorm(x), type="l", col="black", ylab="",
main="Black is standard normal, others are dtikuv(x, d)")
lines(x, dtikuv(x, d=-10), col="red")
lines(x, dtikuv(x, d=-1 ), col="blue")
lines(x, dtikuv(x, d= 1 ), col="green")
legend(2, 0.35, col=c("red","blue","green"), lty=rep(1, len=3),
legend=paste("d =", c(-10, -1, 1)))
plot(x, pnorm(x), type="l", col="black", ylab="",
main="Black is standard normal, others are ptikuv(x, d)")
lines(x, ptikuv(x, d=-10), col="red")
lines(x, ptikuv(x, d=-1 ), col="blue")
lines(x, ptikuv(x, d= 1 ), col="green")
legend(2, 0.35, col=c("red","blue","green"), lty=rep(1, len=3),
legend=paste("d =", c(-10, -1, 1)))
probs = seq(0.1, 0.9, by=0.1)
ptikuv(qtikuv(p=probs, d= 1), d=1) - probs # Should be all 0
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