Package: bltm 0.1.0

Julio Trecenti

bltm: Bayesian Latent Threshold Modeling

Fits latent threshold model for simulated data and describes how to adjust model using real data. Implements algorithm proposed by Nakajima and West (2013) <doi:10.1080/07350015.2012.747847>. This package has a function to generate data, a function to configure priors and a function to fit the model. Examples may be checked inside the demonstration files.

Authors:Julio Trecenti [cre], Fernando Tassinari [aut], Daniel Falbel [ctb]

bltm_0.1.0.tar.gz
bltm_0.1.0.zip(r-4.5)bltm_0.1.0.zip(r-4.4)bltm_0.1.0.zip(r-4.3)
bltm_0.1.0.tgz(r-4.4-any)bltm_0.1.0.tgz(r-4.3-any)
bltm_0.1.0.tar.gz(r-4.5-noble)bltm_0.1.0.tar.gz(r-4.4-noble)
bltm_0.1.0.tgz(r-4.4-emscripten)bltm_0.1.0.tgz(r-4.3-emscripten)
bltm.pdf |bltm.html✨
bltm/json (API)

# Install 'bltm' in R:

install.packages('bltm', repos = c('https://curso-r.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/curso-r/bltm/issues

On CRAN:

2.70 score 1 stars 186 downloads 3 exports 8 dependencies

Last updated 4 years agofrom:20304d4a78. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 11 2024
R-4.5-win	OK	Nov 11 2024
R-4.5-linux	OK	Nov 11 2024
R-4.4-win	OK	Nov 11 2024
R-4.4-mac	OK	Nov 11 2024
R-4.3-win	OK	Nov 11 2024
R-4.3-mac	OK	Nov 11 2024