Package: bgw 0.1.3
David S. Bunch
bgw: Bunch-Gay-Welsch Statistical Estimation
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) <doi:10.1145/151271.151279>. 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 <http://www.apollochoicemodelling.com>). 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 <https://authors.acm.org/author-resources/author-rights>. The main requirement is clear citation of the original publication (see above).
Authors:
bgw_0.1.3.tar.gz
bgw_0.1.3.tar.gz(r-4.5-noble)bgw_0.1.3.tar.gz(r-4.4-noble)
bgw_0.1.3.tgz(r-4.4-emscripten)
bgw.pdf |bgw.html✨
bgw/json (API)
NEWS
# Install 'bgw' in R: |
install.packages('bgw', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:c2a2f7d3dd. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 03 2024 |
R-4.5-linux-x86_64 | OK | Dec 03 2024 |
Exports:bgw_checkSettingbgw_drglgbgw_itsumbgw_mlebgw_mle_setupbgw_writeIterationsdivset_cdrglg_c
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
bgw_checkSetting | bgw_checkSetting |
bgw_drglg | bgw_drglg |
bgw_itsum | bgw_itsum |
bgw_mle | bgw_mle |
bgw_mle_setup | bgw_mle_setup |
Writes the vector [beta,ll] to a file called 'modelname_iterations.csv' # Was created using apollo_writeTheta as a starting point... Because this is an internal function, the inputs will be assumed to be clean. | bgw_writeIterations |