
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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