dllogis(x, shape=1, scale=1, log = FALSE)
pllogis(q, shape=1, scale=1, lower.tail = TRUE, log.p = FALSE)
qllogis(p, shape=1, scale=1, lower.tail = TRUE, log.p = FALSE)
rllogis(n, shape=1, scale=1)
hllogis(x, shape=1, scale=1, log=FALSE)
Hllogis(x, shape=1, scale=1, log=FALSE)length(n) > 1, the length
is taken to be the number required.dllogis gives the density,
pllogis gives the distribution function,
qllogis gives the quantile function,
hllogis gives the hazard function,
Hllogis gives the cumulative hazard function, and
rllogis generates random deviates.shape parameter $a>0$ and
scale parameter $b>0$ has probability density function
$$f(x | a, b) = (a/b) (x/b)^{a-1} / (1 + (x/b)^a)^2$$
and hazard
$$h(x | a, b) = (a/b) (x/b)^{a-1} / (1 + (x/b)^a)$$
for $x>0$. The hazard is decreasing for shape $a\leq 1$, and unimodal for $a > 1$.
The probability distribution function is
$$F(x | a, b) = 1 - 1 / (1 + (x/b)^a)$$
If $a > 1$, the mean is $b c / sin(c)$, and
if $a > 2$ the variance is $b^2 * (2*c/sin(2*c) -
c^2/sin(c)^2)$, where $c = \pi/a$, otherwise these are undefined.dweibull