Package: snreg 1.2.0
Oleg Badunenko
snreg: Regression with Skew-Normally Distributed Error Term
Models with skew‑normally distributed and thus asymmetric error terms, implementing the methods developed in Badunenko and Henderson (2023) "Production analysis with asymmetric noise" <doi:10.1007/s11123-023-00680-5>. The package provides tools to estimate regression models with skew‑normal error terms, allowing both the variance and skewness parameters to be heteroskedastic. It also includes a stochastic frontier framework that accommodates both i.i.d. and heteroskedastic inefficiency terms.
Authors:
snreg_1.2.0.tar.gz
snreg_1.2.0.tar.gz(r-4.7-arm64)snreg_1.2.0.tar.gz(r-4.7-x86_64)snreg_1.2.0.tar.gz(r-4.6-arm64)snreg_1.2.0.tar.gz(r-4.6-x86_64)
snreg_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
snreg/json (API)
NEWS
| # Install 'snreg' in R: |
| install.packages('snreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/olegbadunenko/snreg/issues
Pkgdown/docs site:https://olegbadunenko.github.io
- banks07 - U.S. Commercial Banks Data
Last updated from:88e4a47fb0. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 162 | ||
| linux-devel-x86_64 | OK | 104 | ||
| source / vignettes | OK | 198 | ||
| linux-release-arm64 | OK | 119 | ||
| linux-release-x86_64 | OK | 113 | ||
| wasm-release | OK | 190 |
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| U.S. Commercial Banks Data | banks07 |
| Extract Model Coefficients | coef.snreg |
| Linear Regression via MLE | lm.mle |
| Print Summary of snreg Results | print.summary.snreg |
| Residuals for snreg Objects | residuals.snreg |
| Linear Regression with Skew-Normal Errors | snreg |
| Stochastic Frontier Model with a Skew-Normally Distributed Error Term | snsf |
| Summary Utility ('su') | su |
| Summary for Skew-Normal Regression Models | summary.snreg |
| Compute Owen's T Function 'T(h, a)' | TOwen |
| Compute Owen's T Function 'T(h, a)' | TOwen1 |
| Extract the Variance-Covariance Matrix | vcov.snreg |