mleLEEW: The MLEs of LEEW

In bistoonh/NewDists: The GOGaG and EEG family of distributions.

Description

This function calculates the MLEs of LEEW distribution.

Usage

mleLEEW(x, model = "LEEW", fitplot = TRUE)

Arguments

x	The value of the first shape parameter. Must be finite.
model	"LEEW" (Log-Extended Exp-Weibull) or "LW" (Log-Weibull) model.
fitplot	Logical; if TRUE, histogram and fitted LEEW density is drawn.

Value

par	The MLEs of parameters.
loglike	The log-likelihood value corresponding to MLEs.
convergence	An integer code. 0 indicates successful completion. To see possible error codes, see the optim function.
KS	Kolmogorov Smirnov test.
AIC	The value of Akaike Information Criterion.
BIC	The value of Bayesian Information Criterion.

Author(s)

Bistoon Hosseini, Mahmoud Afshari

References

Alizadeh, Morad, Mahmoud Afshari, Bistoon Hosseini, and Thiago G. Ramires. "Extended exp-G family of distributions: Properties, applications and simulation." Communications in Statistics-Simulation and Computation (2018): 1-16.

Examples

set.seed(100)
x = runif(n = 200, 0, 10)
x = log(x)
mleLEEW(x, model = "LW", fitplot = TRUE)
mleLEEW(x, model = "LEEW", fitplot = TRUE)

bistoonh/NewDists documentation built on May 21, 2019, 11:09 a.m.