LLOGIS: Log-Logistic Distribution

Description Usage Arguments Details Value See Also Examples

Description

Density, distribution function, quantile function and random generation for the log-logistic distribution with shape and scale parameters equal to shape and scale, respectively.

Usage

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dllog(x,shape=1,scale=1,log=FALSE)
pllog(q,shape=1,scale=1,lower.tail=TRUE,log.p=FALSE)
qllog(p,shape=1,scale=1,lower.tail=TRUE,log.p=FALSE)
rllog(n,shape=1,scale=1)

Arguments

x,q

vector of quantiles.

p

vector of probabilities.

n

number of observations.

shape

shape parameter.

scale

scale parameter.

log,log.p

logical; if TRUE, probabilities p are given as log(p).

lower.tail

logical; if TRUE (default), probabilities are P[X <= x],otherwise, P[X > x].

Details

If Y is a random variable distributed according to a logistic distribution (with location and scale parameters), then X = exp(Y) has a log-logistic distribution with shape and scale parameters corresponding to the scale and location parameteres of Y, respectively.

Value

dllog gives the density, pllog gives the distribution function, qllog gives the quantile function, and rllog generates random deviates.

See Also

dlogis, plogis, qlogis, rlogis

Examples

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x <- rllog(10,1,0)
dllog(x,1,0)
dlogis(log(x),0,1)/x

Example output

 [1] 0.25547774 0.21665790 0.82627457 0.18992433 0.00221707 0.82639677
 [7] 0.99281979 0.54178012 0.03052683 0.72120197
 [1] 0.25547774 0.21665790 0.82627457 0.18992433 0.00221707 0.82639677
 [7] 0.99281979 0.54178012 0.03052683 0.72120197

FAdist documentation built on April 17, 2020, 1:24 a.m.