dtikuv(x, d, mean=0, sigma=1, log=FALSE)
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
.log=TRUE
then the logarithm of the density is returned.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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