genlog_simu_sk: Simulating the Generalized logistic distribution with...

In pinduzera/genlogis: Generalized Logistic Distribution

Simulating the Generalized logistic distribution with skewness

Description

Creating a simulation of the generalized logistic distribution with skewness maximum likelihood estimation of the parameters with parallelized processing code using the foreach package.

Usage

genlog_simu_sk(real.par, init.par, sample.size = 100,
            k = 1000, seed = 555, threads = 1, progress.bar = T)

Arguments

real.par	the real parameters value of the distribution wich the random sample will be taken. It has to be a vector of length 5, the parameters are the values of c(a, b, p, mu) as listed in rgenlog, mu can be omitted and will be set to 0. There are no default values.
init.par	Initial values for the parameters to be optimized over in the following order c(a, b, p, mu, skew). Can be an object returned by genlog_slider. There are no default values.
sample.size	the sample size to be taken in each k simulation.
k	the number of simulations.
seed	seed to be given to set.seed() function during the sampling process
threads	the numbers of CPU threads to be used for parallel computing. If the threads number is higher than the available the maximum allowed will be used.
progress.bar	show progress bar for each thread during simulations, default value TRUE.

Details

The used distribution for this package is given by:

f(x) = 2*((a + b*(1+p)*(abs(x-mu)^p))*exp(-(x-mu)*(a+b*(abs(x-mu)^p))))/ ((exp(-(x-mu)*(a + b* (abs(x-mu)^p)))+1)^2) * ((exp(-(skew*(x-mu))*(a+b*(abs(skew*(x-mu))^p)))+1)^(-1))

Value

It returns a data.frame with k rows (each simulation) and 7 columns with the following information:
a, b, p and mu are estimations using maximum likelihood estimation, for more info help(genlogis_mle)
sample.size The sample size used for each k simulation.
convergence The estimation's convergence status.

References

Rathie, P. N. and Swamee, P. K (2006) On a new invertible generalized logistic distribution approximation to normal distribution, Technical Research Report in Statistics, 07/2006, Dept. of Statistics, Univ. of Brasilia, Brasilia, Brazil.

Azzalini, A. (1985) A class of distributions which includes the normal ones. Scandinavian Journal of Statistics.

Examples

genlog_simu_sk(real.par = c(0.3, 0.9, 1.5, 0.0, .9), init.par = c(0.9, 0.3, 0.2, 0.0, .9), 
            sample.size = 100, k = 50, threads = 2, seed = 200) 

pinduzera/genlogis documentation built on Feb. 12, 2024, 3:30 a.m.