Density, distribution function, quantile function, and random generation for the logarithmic distribution.
dlog(x, shape, log = FALSE)
plog(q, shape, log.p = FALSE)
qlog(p, shape)
rlog(n, shape)
Same interpretation as in runif
.
The shape parameter value logff
.
Logical.
If log.p = TRUE
then all probabilities p
are
given as log(p)
.
dlog
gives the density,
plog
gives the distribution function,
qlog
gives the quantile function, and
rlog
generates random deviates.
The details are given in logff
.
Forbes, C., Evans, M., Hastings, N. and Peacock, B. (2011) Statistical Distributions, Hoboken, NJ, USA: John Wiley and Sons, Fourth edition.
# NOT RUN {
dlog(1:20, 0.5)
rlog(20, 0.5)
# }
# NOT RUN {
shape <- 0.8; x <- 1:10
plot(x, dlog(x, shape = shape), type = "h", ylim = 0:1,
sub = "shape=0.8", las = 1, col = "blue", ylab = "shape",
main = "Logarithmic distribution: blue=density; orange=distribution function")
lines(x + 0.1, plog(x, shape = shape), col = "orange", lty = 3, type = "h")
# }
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