Other packages > Find by keyword >

bgw  

Bunch-Gay-Welsch Statistical Estimation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("bgw", "0.1.3")



Attach the package and use:
library("bgw")
Maintained by
David S. Bunch
[Scholar Profile | Author Map]
First Published: 2022-12-22
Latest Update: 2023-07-13
Description:
Performs statistical estimation and inference-related computations by accessing and executing modified versions of 'Fortran' subroutines originally published in the Association for Computing Machinery (ACM) journal Transactions on Mathematical Software (TOMS) by Bunch, Gay and Welsch (1993) . The acronym 'BGW' (from the authors' last names) will be used when making reference to technical content (e.g., algorithm, methodology) that originally appeared in ACM TOMS. A key feature of BGW is that it exploits the special structure of statistical estimation problems within a trust-region-based optimization approach to produce an estimation algorithm that is much more effective than the usual practice of using optimization methods and codes originally developed for general optimization. The 'bgw' package bundles 'R' wrapper (and related) functions with modified 'Fortran' source code so that it can be compiled and linked in the 'R' environment for fast execution. This version implements a function ('bgw_mle.R') that performs maximum likelihood estimation (MLE) for a user-provided model object that computes probabilities (a.k.a. probability densities). The original motivation for producing this package was to provide fast, efficient, and reliable MLE for discrete choice models that can be called from the 'Apollo' choice modelling 'R' package ( see ). Starting with the release of Apollo 3.0, BGW is the default estimation package. However, estimation can also be performed using BGW in a stand-alone fashion without using 'Apollo' (as shown in simple examples included in the package). Note also that BGW capabilities are not limited to MLE, and future extension to other estimators (e.g., nonlinear least squares, generalized method of moments, etc.) is possible. The 'Fortran' code included in 'bgw' was modified by one of the original BGW authors (Bunch) under his rights as confirmed by direct consultation with the ACM Intellectual Property and Rights Manager. See . The main requirement is clear citation of the original publication (see above).
How to cite:
David S. Bunch (2022). bgw: Bunch-Gay-Welsch Statistical Estimation. R package version 0.1.3, https://cran.r-project.org/web/packages/bgw. Accessed 05 Apr. 2025.
Previous versions and publish date:
0.1.0 (2022-12-22 21:00), 0.1.1 (2023-04-06 19:50), 0.1.2 (2023-07-13 16:30)
Other packages that cited bgw R package
View bgw citation profile
Other R packages that bgw depends, imports, suggests or enhances
Complete documentation for bgw
Functions, R codes and Examples using the bgw R package
Some associated functions: bgw-internal . bgw_checkSetting . bgw_drglg . bgw_itsum . bgw_mle . bgw_mle_setup . bgw_writeIterations . 
Some associated R codes: bgw_checkSetting.R . bgw_drglg.R . bgw_itsum.R . bgw_mle.R . bgw_mle_setup.R . bgw_writeIterations.R .  Full bgw package functions and examples
Downloads during the last 30 days
03/0603/0703/0803/0903/1003/1103/1203/1303/1403/1503/1603/1703/1803/1903/2003/2103/2203/2303/2403/2503/2603/2703/2803/2903/3003/3104/0104/0204/0304/04Downloads for bgw102030405060708090100110TrendBars

Today's Hot Picks in Authors and Packages

deepdive  
Deep Learning for General Purpose
Aims to provide simple intuitive functions to create quick prototypes of artificial neural network o ...
Download / Learn more Package Citations See dependency  
IGST  
Informative Gene Selection Tool
Mining informative genes with certain biological meanings are important for clinical diagnosis of di ...
Download / Learn more Package Citations See dependency  
gllvm  
Generalized Linear Latent Variable Models
Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation i ...
Download / Learn more Package Citations See dependency  
TrendInTrend  
Odds Ratio Estimation and Power Calculation for the Trend in Trend Model
Estimation of causal odds ratio and power calculation given trends in exposure prevalenceand outcome ...
Download / Learn more Package Citations See dependency  
leapp  
Latent Effect Adjustment After Primary Projection
These functions take a gene expression value matrix, a primary covariate vector, an additional know ...
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  

23,990

R Packages

207,311

Dependencies

64,809

Author Associations

23,991

Publication Badges

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