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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]
All associated links for this package
First Published: 2022-12-22
Latest Update: 2024-03-29
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 07 Mar. 2026.
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), 0.1.3 (2024-03-29 15:50)
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
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