Package: brtobit 0.1-2
brtobit: Bias-Reduced Tobit Regression
Tobit models are regression models with a Gaussian response variable left-censored at zero, constant latent variance, and a latent mean that depends on covariates through a linear predictor. As an alternative to plain maximum likelihood estimation, the adjusted score equations of Kosmidis and Firth (2010) <doi:10.1214/10-ejs579> are utilized to obtain bias-reduced estimates of the model parameters.
Authors:
brtobit_0.1-2.tar.gz
brtobit_0.1-2.zip(r-4.5)brtobit_0.1-2.zip(r-4.4)brtobit_0.1-2.zip(r-4.3)
brtobit_0.1-2.tgz(r-4.4-any)brtobit_0.1-2.tgz(r-4.3-any)
brtobit_0.1-2.tar.gz(r-4.5-noble)brtobit_0.1-2.tar.gz(r-4.4-noble)
brtobit_0.1-2.tgz(r-4.4-emscripten)brtobit_0.1-2.tgz(r-4.3-emscripten)
brtobit.pdf |brtobit.html✨
brtobit/json (API)
| # Install 'brtobit' in R: |
| install.packages('brtobit', repos = c('https://zeileis.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/topmodels
Last updated 3 days agofrom:06b70d6fea. Checks:OK: 7. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 16 2024 |
| R-4.5-win | OK | Sep 16 2024 |
| R-4.5-linux | OK | Sep 16 2024 |
| R-4.4-win | OK | Sep 16 2024 |
| R-4.4-mac | OK | Sep 16 2024 |
| R-4.3-win | OK | Sep 16 2024 |
| R-4.3-mac | OK | Sep 16 2024 |
Exports:brtobitbrtobit_controlbrtobit_fit
Dependencies:crchevaluateFormulahighrknitrlatticeMASSMatrixnlmenumDerivordinalRcppRcppArmadillosandwichscoringRulesucminfxfunyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bias-Reduced Tobit Regression | bread.brtobit brtobit brtobit_control brtobit_fit coef.brtobit fitted.brtobit getSummary.brtobit logLik.brtobit model.frame.brtobit model.matrix.brtobit predict.brtobit print.brtobit print.summary.brtobit prodist.brtobit summary.brtobit vcov.brtobit |
