Package: glsm 0.0.0.6
Jorge Villalba
glsm: Saturated Model Log-Likelihood for Multinomial Outcomes
When the response variable Y takes one of R > 1 values, the function 'glsm()' computes the maximum likelihood estimates (MLEs) of the parameters under four models: null, complete, saturated, and logistic. It also calculates the log-likelihood values for each model. This method assumes independent, non-identically distributed variables. For grouped data with a multinomial outcome, where observations are divided into J populations, the function 'glsm()' provides estimation for any number K of explanatory variables.
Authors:
glsm_0.0.0.6.tar.gz
glsm_0.0.0.6.tar.gz(r-4.7-any)glsm_0.0.0.6.tar.gz(r-4.6-any)
glsm_0.0.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
glsm/json (API)
| # Install 'glsm' in R: |
| install.packages('glsm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- hsbdemo - Hsbdemo: School data for testing.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b8569e9f4a. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 122 | ||
| source / vignettes | OK | 150 | ||
| linux-release-x86_64 | OK | 115 | ||
| wasm-release | OK | 108 |
Exports:glsm
Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigplyrR6RColorBrewerRcpprlangS7scalestibbletidyselectutf8vctrsVGAMviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence Intervals for Coefficients in 'glsm' Objects | confint.glsm |
| Saturated Model Log-Likelihood for Multinomial Outcomes | glsm |
| hsbdemo: School data for testing. | hsbdemo |
| Summary Method for in 'glsm' Objects | summary.glsm |