Brief introduction | Choosing between bessel regression and beta regression | Using the bbreg package | Fitting bbreg (bessel or beta regression) models | Viewing summaries | Changing link functions | Getting fitted values | Making predictions | Creating simulated envelopes | Diagnostic plots for bbreg objects
Package: bbreg 2.0.2
Vinicius Mayrink
bbreg: Bessel and Beta Regressions via Expectation-Maximization Algorithm for Continuous Bounded Data
Functions to fit, via Expectation-Maximization (EM) algorithm, the Bessel and Beta regressions to a data set with a bounded continuous response variable. The Bessel regression is a new and robust approach proposed in the literature. The EM version for the well known Beta regression is another major contribution of this package. See details in the references Barreto-Souza, Mayrink and Simas (2022) <doi:10.1111/anzs.12354> and Barreto-Souza, Mayrink and Simas (2020) <arxiv:2003.05157>.
Authors:
bbreg_2.0.2.tar.gz
bbreg_2.0.2.tar.gz(r-4.7-any)bbreg_2.0.2.tar.gz(r-4.6-any)
bbreg_2.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bbreg/json (API)
| # Install 'bbreg' in R: |
| install.packages('bbreg', 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 from:cb22d2d4a7. Checks:2 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 118 | ||
| source / vignettes | OK | 251 | ||
| linux-release-x86_64 | NOTE | 110 | ||
| wasm-release | OK | 100 |
