distname-utils: Utilities for distributions supported in this package

distname-utilsR Documentation

Utilities for distributions supported in this package

Description

The Lambert W\times F framework can take any (continuous) random variable with distribution F and make it skewed (type = "s"), heavy tailed (type = "h"), or both (type = "hh").

In principle, this works for any F. Of course, this package implements only a finite number of distributions, which can be specified with the distname argument. Most functions in this package, however, also allow you to pass your own distribution and parameters and create a Lambert W\times F version of it.

check_distname checks if the distribution specified by the distname argument is implemented in this package.

get_distname_family determines whether a distribution is a location, scale, or location-scale family. It also returns whether the distribution is supported on non-negative values only.

get_distnames lists all currently implemented distributions F_X.

Usage

check_distname(distname)

get_distname_family(distname)

get_distnames()

Arguments

distname

character; name of input distribution; see get_distnames.

Value

check_distname returns (invisible) that the distribution is implemented, or throws an error otherwise.

get_distname_family returns a list with

location

logical; if TRUE, the distribution is a location family,

scale

logical; if TRUE, the distribution is a scale family.

is.non.negative

logical; if TRUE, the distribution has support only for the non-negative reals (this is usually the case when location = FALSE and scale = TRUE)

get_distnames returns a vector of strings in alphabetical order. It lists all supported distributions. Each string can be passed as the distname argument to several functions in this package.

See Also

create_LambertW_input, create_LambertW_output.

Examples


check_distname("normal")
## Not run: 
check_distname("my_great_distribution")

## End(Not run)

get_distname_family("normal")

LambertW documentation built on Sept. 22, 2022, 5:07 p.m.