VGAM: paralogisticUC – R documentation

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paralogisticUC

The Paralogistic Distribution

Description

Density, distribution function, quantile function and random generation for the paralogistic distribution with shape parameter a and scale parameter scale.

Usage

dparalogistic(x, scale = 1, shape1.a, log = FALSE)
pparalogistic(q, scale = 1, shape1.a, lower.tail = TRUE, log.p = FALSE)
qparalogistic(p, scale = 1, shape1.a, lower.tail = TRUE, log.p = FALSE)
rparalogistic(n, scale = 1, shape1.a)

Arguments

`x, q`	vector of quantiles.
`p`	vector of probabilities.
`n`	number of observations. If `length(n) > 1`, the length is taken to be the number required.
`shape1.a`	shape parameter.
`scale`	scale parameter.
`log`	Logical. If `log=TRUE` then the logarithm of the density is returned.
`lower.tail, log.p`	Same meaning as in `pnorm` or `qnorm`.

Details

See paralogistic, which is the VGAM family function for estimating the parameters by maximum likelihood estimation.

Value

dparalogistic gives the density, pparalogistic gives the distribution function, qparalogistic gives the quantile function, and rparalogistic generates random deviates.

Note

The paralogistic distribution is a special case of the 4-parameter generalized beta II distribution.

Author(s)

T. W. Yee and Kai Huang

References

Kleiber, C. and Kotz, S. (2003). Statistical Size Distributions in Economics and Actuarial Sciences, Hoboken, NJ, USA: Wiley-Interscience.

Examples

pdata <- data.frame(y = rparalogistic(n = 3000, scale = exp(1), exp(2)))
fit <- vglm(y ~ 1, paralogistic(lss = FALSE, ishape1.a = 4.1),
            data = pdata, trace = TRUE)
coef(fit, matrix = TRUE)
Coef(fit)

VGAM

Vector Generalized Linear and Additive Models

v1.1-5

GPL-3

Authors

Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)

Initial release

2021-01-13