
dlog(x, prob)
plog(q, prob, log.p=FALSE)rlog(n, prob, Smallno=1.0e-6)
logff
.
Here it is called prob
because $0TRUE
then all probabilities p
are given as log(p)
.plog(U, prob) > 1-Smallno
where U
is the upper limit.dlog
gives the density,
plog
gives the distribution function, and rlog
generates random deviates.logff
.logff
.dlog(1:20, 0.5)
rlog(20, 0.5)
prob = 0.8; x = 1:10
plot(x, dlog(x, prob=prob), type="h", ylim=0:1,
sub="prob=0.8", las=1, col="blue", ylab="Probability",
main="Logarithmic distribution: blue=density; red=distribution function")
lines(x+0.1, plog(x, prob=prob), col="red", lty=3, type="h")
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