Other packages > Find by keyword >

GB2  

Generalized Beta Distribution of the Second Kind: Properties, Likelihood, Estimation
View on CRAN: Click here


Download and install GB2 package within the R console
Install from CRAN:
install.packages("GB2")

Install from Github:
library("remotes")
install_github("cran/GB2")

Install by package version:
library("remotes")
install_version("GB2", "2.1.2")



Attach the package and use:
library("GB2")
Maintained by
Desislava Nedyalkova
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-01-06
Latest Update: 2025-09-01
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.
How to cite:
Desislava Nedyalkova (2011). GB2: Generalized Beta Distribution of the Second Kind: Properties, Likelihood, Estimation. R package version 2.1.2, https://cran.r-project.org/web/packages/GB2. Accessed 07 Oct. 2026.
Previous versions and publish date:
1.0 (2011-01-06 21:42), 1.1 (2012-08-31 15:39), 1.2 (2014-06-25 23:57), 2.1.1 (2022-06-22 07:53), 2.1 (2015-05-11 23:48), (2026-07-09 08:04)
Other packages that cited GB2 R package
View GB2 citation profile
Other R packages that GB2 depends, imports, suggests or enhances
Complete documentation for GB2
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

plaqr  
Partially Linear Additive Quantile Regression
Estimation, prediction, thresholding, transformation, and plotting for partially linear additive qua ...
Download / Learn more Package Citations See dependency  
splm  
Econometric Models for Spatial Panel Data
ML and GM estimation and diagnostic testing of econometric models for spatial panel data. ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
blandr  
Bland-Altman Method Comparison
Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM B ...
Download / Learn more Package Citations See dependency  
ggTimeSeries  
Time Series Visualisations Using the Grammar of Graphics
Provides additional display mediums for time series visualisations. ...
Download / Learn more Package Citations See dependency  
PairedData  
Paired Data Analysis
Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis test ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA