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location.ald
, scale parameter scale.ald
(on the log scale),
and asymmetry parameter kappa
.dloglap(x, location.ald=0, scale.ald=1,
tau=0.5, kappa=sqrt(tau/(1-tau)), log=FALSE)
ploglap(q, location.ald=0, scale.ald=1,
tau=0.5, kappa=sqrt(tau/(1-tau)))
qloglap(p, location.ald=0, scale.ald=1,
tau=0.5, kappa=sqrt(tau/(1-tau)))
rloglap(n, location.ald=0, scale.ald=1,
tau=0.5, kappa=sqrt(tau/(1-tau)))
length(n) > 1
then the length is taken to be the number required.kappa
and is ignored
if kappa
is assigned.TRUE
, probabilities p
are given as log(p)
.dloglap
gives the density,
ploglap
gives the distribution function,
qloglap
gives the quantile function, and
rloglap
generates random deviates.alaplace3
.dalap
,
alaplace3
, loglaplace1
.loc = 0; sigma = exp(0.5); kappa = 1
x = seq(-0.2, 5, by=0.01)
plot(x, dloglap(x, loc, sigma, kappa=kappa), type="l", col="blue",
main="Blue is density, red is cumulative distribution function",
ylim=c(0,1), sub="Purple are 5,10,...,95 percentiles", las=1, ylab="")
abline(h=0, col="blue", lty=2)
lines(qloglap(seq(0.05,0.95,by=0.05), loc, sigma, kappa=kappa),
dloglap(qloglap(seq(0.05,0.95,by=0.05), loc, sigma, kappa=kappa),
loc, sigma, kappa=kappa), col="purple", lty=3, type="h")
lines(x, ploglap(x, loc, sigma, kappa=kappa), type="l", col="red")
abline(h=0, lty=2)
ploglap(qloglap(seq(0.05,0.95,by=0.05), loc, sigma, kappa=kappa),
loc, sigma, kappa=kappa)
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