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GB2 (version 2.1.1)

Generalized Beta Distribution of the Second Kind: Properties, Likelihood, Estimation

Description

Package GB2 explores the Generalized Beta distribution of the second kind. Density, cumulative distribution function, quantiles and moments of the distributions are given. Functions for the full log-likelihood, the profile log-likelihood and the scores are provided. Formulas for various indicators of inequality and poverty under the GB2 are implemented. The GB2 is fitted by the methods of maximum pseudo-likelihood estimation using the full and profile log-likelihood, and non-linear least squares estimation of the model parameters. Various plots for the visualization and analysis of the results are provided. Variance estimation of the parameters is provided for the method of maximum pseudo-likelihood estimation. A mixture distribution based on the compounding property of the GB2 is presented (denoted as "compound" in the documentation). This mixture distribution is based on the discretization of the distribution of the underlying random scale parameter. The discretization can be left or right tail. Density, cumulative distribution function, moments and quantiles for the mixture distribution are provided. The compound mixture distribution is fitted using the method of maximum pseudo-likelihood estimation. The fit can also incorporate the use of auxiliary information. In this new version of the package, the mixture case is complemented with new functions for variance estimation by linearization and comparative density plots.

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Version

Install

install.packages('GB2')

Monthly Downloads

328

Version

2.1.1

License

GPL (>= 2)

Maintainer

Desislava Nedyalkova

Last Published

June 22nd, 2022

Functions in GB2 (2.1.1)

CompoundMoments

Moments of the Compound Distribution based on the GB2
CompoundDensPlot

Comparison of the GB2, compound GB2 and kernel densities
CompoundAuxDensPlot

Comparison of the compound GB2 and kernel densities by group
CompoundQuantiles

Quantiles and random generation of the Compound Distribution based on the GB2
CompoundAuxVarest

Variance Estimation under the Compound GB2 Distribution Using Auxiliary Information
CompoundAuxFit

Fitting the Compound Distribution based on the GB2 by the Method of Pseudo Maximum Likelihood Estimation using Auxiliary Information
CompoundIndicators

Indicators of Poverty and Social Exclusion under the Compound Distribution based on the GB2
CompoundFit

Fitting the Compound Distribution based on the GB2 by the Method of Maximum Likelihood Estimation
Compound

Compound Distribution based on the Generalized Beta Distribution of the Second Kind
LogLikelihood

Full Log-likelihood of the GB2 Distribution
Indicators

Monetary Laeken Indicators under the GB2
CompoundVarest

Variance Estimation of the Compound GB2 Distribution
MLfullGB2

Maximum Likelihood Estimation of the GB2 Based on the Full Log-likelihood
MLfitGB2

Fitting the GB2 by the Method of Maximum Likelihood Estimation and Comparison of the Fitted Indicators with the Empirical Indicators
MLprofGB2

Maximum Likelihood Estimation of the GB2 Based on the Profile Log-likelihood
Contindic

Sensitivity Analysis of Laeken Indicators on GB2 Parameters
Moments

Moments and Other Properties of a GB2 Random Variable
Gini

Computation of the Gini Coefficient for the GB2 Distribution and its Particular Cases.
NonlinearFit

Fitting the GB2 by Minimizing the Distance Between a Set of Empirical Indicators and Their GB2 Expressions
LogDensity

Log Density of the GB2 Distribution
PlotsML

Cumulative Distribution Plot and Kernel Density Plot for the Fitted GB2
Varest

Variance Estimation of the Parameters of the GB2 Distribution
Fisk

Parameters of the Fisk Distribution
gb2

The Generalized Beta Distribution of the Second Kind
Contprof

Contour Plot of the Profile Log-likelihood of the GB2 Distribution
RobustWeights

Robustification of the sampling weights
ProfLogLikelihood

Profile Log-likelihood of the GB2 Distribution
Thomae

Maximum Excess Representation of a Generalized Hypergeometric Function Using Thomae's Theorem