a
and p
, and scale parameter scale
.dinv.paralogistic(x, scale = 1, shape1.a, log = FALSE)
pinv.paralogistic(q, scale = 1, shape1.a, lower.tail = TRUE, log.p = FALSE)
qinv.paralogistic(p, scale = 1, shape1.a, lower.tail = TRUE, log.p = FALSE)
rinv.paralogistic(n, scale = 1, shape1.a)
length(n) > 1
, the length
is taken to be the number required.log = TRUE
then the logarithm of the density is returned.dinv.paralogistic
gives the density,
pinv.paralogistic
gives the distribution function,
qinv.paralogistic
gives the quantile function, and
rinv.paralogistic
generates random deviates.inv.paralogistic
, which is the inv.paralogistic
,
genbetaII
.idata <- data.frame(y = rinv.paralogistic(n = 3000, exp(1), scale = exp(2)))
fit <- vglm(y ~ 1, inv.paralogistic(lss = FALSE, ishape1.a = 2.1),
data = idata, trace = TRUE, crit = "coef")
coef(fit, matrix = TRUE)
Coef(fit)
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