Random Sampling of K-th Order Statistics from a Generalized Log-gamma Distribution
Random Sampling of K-th Order Statistics from a Generalized Log-gamma Distribution
order_glg is used to obtain a random sample of the K-th order statistics from a generalized log-gamma distribution.
order_glg(size, mu, sigma, lambda, k, n, alpha =0.05)
Arguments
size: numeric, represents the size of the sample.
mu: numeric, represents the location parameter. Default value is 0.
sigma: numeric, represents the scale parameter. Default value is 1.
lambda: numeric, represents the shape 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.
alpha: numeric, (1 - alpha) represents the confidence of an interval for the population median of the distribution of the k-th order statistic. Default value is 0.05.
Returns
A list with a random sample of order statistics from a generalized log-gamma distribution, the value of its join probability density function evaluated in the random sample and a (1 - alpha) confidence interval for the population median of the distribution of the k-th order statistic.
Examples
# A random sample of size 10 of order statistics from a Extreme Value Distribution.order_glg(10,0,1,1,1,50)## Not run:# A small comparison between two random sampling methods of order statistics# Method 1m <-10output <- rep(0,m)order_sample <-function(m,n,k){for(i in1:m){sample <- rglg(n)order_sample <- sort(sample)output[i]<- order_sample[k]}return(output)}N <-10000n <-200k <-100system.time(order_sample(N,n,k))sample_1 <- order_sample(N,n,k)hist(sample_1)summary(sample_1)# Method 2system.time(order_glg(N,0,1,1,k,n))sample_2 <- order_glg(N,0,1,1,k,n)$sample
hist(sample_2)summary(sample_2)## End(Not run)
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.