ALoD: Quantile-based asymmetric logistic distribution

In QBAsyDist: Asymmetric Distributions and Quantile Estimation

Description

Density, cumulative distribution function, quantile function and random sample generation from the quantile-based asymmetric logistic distribution (ALoD) proposed in Gijbels et al. (2019a).

Usage

dALoD(y, mu, phi, alpha)

pALoD(q, mu, phi, alpha)

qALoD(beta, mu, phi, alpha)

rALoD(n, mu, phi, alpha)

Arguments

y, q	These are each a vector of quantiles.
mu	This is the location parameter μ.
phi	This is the scale parameter φ.
alpha	This is the index parameter α.
beta	This is a vector of probabilities.
n	This is the number of observations, which must be a positive integer that has length 1.

Value

dALoD provides the density, pALoD provides the cumulative distribution function, qALoD provides the quantile function, and rALoD generates a random sample from the quantile-based asymmetric logistic distribution. The length of the result is determined by n for rALoD, and is the maximum of the lengths of the numerical arguments for the other functions.

References

Gijbels, I., Karim, R. and Verhasselt, A. (2019a). On quantile-based asymmetric family of distributions: properties and inference. International Statistical Review, https://doi.org/10.1111/insr.12324.

See Also

dQBAD, pQBAD, qQBAD, rQBAD

Examples

# Quantile-based asymmetric logistic distribution (ALoD)
# Density
rnum<-rnorm(100)
dALoD(y=rnum,mu=0,phi=1,alpha=.5)

# Distribution function
pALoD(q=rnum,mu=0,phi=1,alpha=.5)

# Quantile function
beta<-c(0.25,0.5,0.75)
qALoD(beta=beta,mu=0,phi=1,alpha=.5)

# random sample generation
rALoD(n=100,mu=0,phi=1,alpha=.5)

QBAsyDist documentation built on Sept. 4, 2019, 1:05 a.m.