order_sinharcsinh: Random Sampling of k-th Order Statistics from a Sinh-Arcsinh...

In orders: Sampling from k-th Order Statistics of New Families of Distributions

Random Sampling of k-th Order Statistics from a Sinh-Arcsinh Distribution

Description

order_sinharcsinh is used to obtain a random sample of the k-th order statistic from a Sinh-Arcsinh Distribution and some associated quantities of interest.

Usage

order_sinharcsinh(size, k, mu, sigma, nu, tau, n, p = 0.5, alpha = 0.05, ...)

Arguments

size	numeric, represents the size of the sample.
k	numeric, represents the K-th smallest value from a sample.
mu	numeric, represents the location parameter values.
sigma	numeric, represents scale parameter values.
nu	numeric, represents skewness parameter values
tau	numeric, represents kurtosis tau parameter values.
n	numeric, represents the size of the sample to compute the order statistic from.
p	numeric, represents the 100p percentile for the distribution of the k-th order statistic. Default value is population median, p = 0.5.
alpha	numeric, (1 - alpha) represents the confidence of an interval for the population percentile p of the distribution of the k-th order statistic. Default value is 0.05.
...	represents others parameters of a Sinh-Arcsinh distribution.

Value

A list with a random sample of order statistics from a Sinh-Arcsinh Distribution, the value of its join probability density function evaluated in the random sample and an approximate (1 - alpha) confidence interval for the population percentile p of the distribution of the k-th order statistic.

Author(s)

Carlos Alberto Cardozo Delgado <[e-mail]>.

References

Gentle, J, Computational Statistics, First Edition. Springer - Verlag, 2009.

Ribgy, R. and Stasinopoulos, M. (2005) Generalized Additive Models for Location Scale and Shape, Journal of the Royal Statistical Society. Applied Statistics, Series C.

Examples

library(orders)
# A sample of size 10 of the 3-th order statistics from a Sinh-Arcsinh Distribution
order_sinharcsinh(size=10,k=3,mu=0,sigma=1,nu=1,tau=2,n=30,p=0.5,alpha=0.02)

orders documentation built on Nov. 14, 2023, 9:07 a.m.