Package: lillardhaz 1.0.0
lillardhaz: Simultaneous-Equations Hazard/Probit Models with a Gaussian-Copula Correlation
Fits two-equation simultaneous models in the style of Lillard (1993) <doi:10.1016/0304-4076(93)90106-F>: a pair of processes, each either a binary probit outcome or a continuous-time hazard duration, linked through a single correlation parameter between their underlying error terms and estimated jointly by maximum likelihood via a Gaussian copula. Equation 1 may be a probit, a log-normal accelerated-failure-time hazard, or a piecewise (linear-log-hazard) Gompertz hazard with an arbitrary, user-specified number of segments; equation 2 is always a hazard, log-normal or piecewise Gompertz. Models can also be fit under independence (correlation fixed at zero), which reduces exactly to two separate univariate fits. See the package vignette/manual for the full likelihood derivation and a simulation-based verification.
Authors:
lillardhaz_1.0.0.tar.gz
lillardhaz_1.0.0.zip(r-4.7-any)lillardhaz_1.0.0.zip(r-4.6-any)
lillardhaz_1.0.0.tar.gz(r-4.7-any)lillardhaz_1.0.0.tar.gz(r-4.6-any)
lillardhaz_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
lillardhaz/json (API)
| # Install 'lillardhaz' in R: |
| install.packages('lillardhaz', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nobifukuda/lillardhaz/issues
Last updated from:313830201b. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 99 | ||
| source / vignettes | OK | 156 | ||
| linux-release | OK | 122 | ||
| windows-devel | OK | 62 | ||
| windows-release | OK | 76 | ||
| wasm-release | OK | 91 |
Exports:fit_lillardhaz
Dependencies:digestgenericslatticemaxLikmiscToolspbivnormsandwichzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| lillardhaz: Simultaneous-Equations Hazard/Probit Models | lillardhaz-package lillardhaz |
| Fit a Lillard-style simultaneous-equations hazard/probit model | fit_lillardhaz |
| Predicted survival/density/index from a fitted lillardhaz model | predict.lillardhaz |
