MLEce

Welcome to MLEce, an R package for asymptotic efficient closed-form estimators for multivariate distributions.

Description

The goal of MLEce is to provide asymptotic efficient closed-form estimators (MLEces) for three multivariate distributions (gamma, Weibull and Dirichlet) whose maximum likelihood estimators (MLEs) are not in closed forms. Closed-form estimators are strong consistent, and have the similar asymptotic normal distribution like MLEs. But the calculation of MLEces are much faster than the corresponding MLEs.

Installation

In the R program, you can install the MLEce package like so:

install.packages(MLEce)
library(MLEce)

Examples

There are basic examples which show you how to solve common problems. For the bivariate gamma distribution, the following example is presented.

library(MLEce)
#bivariate gamma distribution
 data_BiGam <-  rBiGam(100, c(1,4,5))
 res_BiGam  <- MLEce(data_BiGam, "BiGam")
 summary(res_BiGam)

For the bivariate Weibull distribution, a real data example is provided as follows.

 #bivariate Weibull distribution
 data(airquality)
 air_data <- airquality[ ,3:4]
 air_data[ ,2] <- air_data[ ,2]*0.1
 est_BiWei <- MLEce(air_data, "BiWei")
 print(est_BiWei)

For the multivariate Dirichlet distribution, an example about the comparison between the MLEce and MLE is given as follows.

 #multivariate Dirichlet distribution
 data_Diri <- LaplacesDemon::rdirichlet(80, c(3,4,1,3,4))
 benchMLEce(data_Diri, distname="Dirichlet", methods=c("MLEce","MLE"))

More commands of the MLEce with corresponding examples can be found in the CRAN.

Licensing

MLEce is licensed for public/open source use under the GNU General Public License, Version 2 (GPL-2).