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dlog(x, prob, log = FALSE)
plog(q, prob, log.p = FALSE)
rlog(n, prob, Smallno = 1.0e-6)
logff
.
Here it is called prob
because $0log.p = TRUE
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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