The logit and invlogit functions, widely used in this package, are wrappers
of qlogis and plogis functions.
Functions eslogis is the expected shortfall of the logistic function
(times a factor 2).
When p<=0.5, it is equivalent (times -1) to the left tail mean ltmlogis.
When p>0.5, it is equivalent to the right tail mean rtmlogis.
ltmlogis and rtmlogis are used to calculate the h parameter
in hkiener1, hkiener2, hkiener3, hkiener4.
Usage
logit(p)
invlogit(x)
ltmlogis(p, m = 0, g = 1, lower.tail = TRUE, log.p = FALSE)
rtmlogis(p, m = 0, g = 1, lower.tail = TRUE, log.p = FALSE)
eslogis(p, m = 0, g = 1, lower.tail = TRUE, log.p = FALSE)
Arguments
p
numeric. one value or a vector between 0 and 1.
x
numeric. one value or a vector of numerics.
m
numeric. a central parameter (also used in model K1, K2, K3 and K4).
g
numeric. a scale parameter (also used in model K1, K2, K3 and K4).
lower.tail
logical. If TRUE, use p. If FALSE, use 1-p.
log.p
logical. If TRUE, probabilities p are given as log(p).
Details
logit function is defined for p in (0, 1) by:
$$ logit(p) = log( p/(1-p) ) $$
invlogit function is defined for x in (-Inf, +Inf) by:
$$ invlogit(x) = exp(x)/(1+exp(x)) = plogis(x) $$