| order_mog {orders} | R Documentation |
Random Sampling of k-th Order Statistics from a Marshall Olkin G Distribution
Description
order_mog is used to obtain a random sample of k-th order statistic from a Marshall Olkin G distribution.
Usage
order_mog(size, spec, beta, k, n, p = 0.5, alpha = 0.05, ...)
Arguments
size |
numeric, represents the size of the sample. |
spec |
character, represents an specific G distribution. Possible values "norm", "exp","lnorm","chisq". |
beta |
numeric, represents the scale parameter. Default value is 1. |
k |
numeric, represents the k-th smallest value from a sample. |
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 the G distribution. |
Value
A list with a random sample of order statistics from a Marshall Olkin G Distribution, the value of its join probability density function evaluated in the random sample and an approximate 100(1 - alpha) confidence interval for the population percentile p of the distribution of the K-th order statistic.
Author(s)
Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>.
References
Gentle, J, Computational Statistics, First Edition. Springer - Verlag, 2009.
Naradajah, S. and Rocha, R. (2016) Newdistns: An R Package for New Families of Distributions, Journal of Statistical Software.
Examples
library(orders)
# A sample of size 10 of the 3-th order statistics from
# a Marshall Olkin Exponential Distribution
order_mog(10,"exp",p=0.5,1,k=3,50,alpha=0.02)
# A sample of size 10 of the 3-th order statistics from
# a Marshall Olkin Normal Distribution
order_mog(10,"norm",p=0.5,1,k=3,50)
# A sample of size 10 of the 3-th order statistics from
# a Marshall Olkin Log-normal Distribution
order_mog(10,"lnorm",p=0.5,1,k=3,50)