Package: Rchoice 0.3-6
Rchoice: Discrete Choice (Binary, Poisson and Ordered) Models with Random Parameters
An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data as presented in Sarrias (2016) <doi:10.18637/jss.v074.i10>.
Authors:
Rchoice_0.3-6.tar.gz
Rchoice_0.3-6.zip(r-4.5)Rchoice_0.3-6.zip(r-4.4)Rchoice_0.3-6.zip(r-4.3)
Rchoice_0.3-6.tgz(r-4.4-any)Rchoice_0.3-6.tgz(r-4.3-any)
Rchoice_0.3-6.tar.gz(r-4.5-noble)Rchoice_0.3-6.tar.gz(r-4.4-noble)
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Rchoice.pdf |Rchoice.html✨
Rchoice/json (API)
NEWS
| # Install 'Rchoice' in R: |
| install.packages('Rchoice', repos = c('https://mauricio1986.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mauricio1986/rchoice/issues
Last updated 2 years agofrom:0f9c3390bf. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 31 2024 |
| R-4.5-win | NOTE | Aug 31 2024 |
| R-4.5-linux | NOTE | Aug 31 2024 |
| R-4.4-win | NOTE | Aug 31 2024 |
| R-4.4-mac | NOTE | Aug 31 2024 |
| R-4.3-win | OK | Aug 31 2024 |
| R-4.3-mac | OK | Aug 31 2024 |
Exports:bread.hetprobbread.ivpmlbread.Rchoicecor.Rchoicecov.Rchoiceeffectestfun.hetprobestfun.ivpmlestfun.Rchoicehetprobis.rFormulaivpmlordinalRchoicese.cov.Rchoice
Dependencies:bdsmatrixcollapsedata.tabledigestexpmFormulagenericsjsonlitelatticelmtestMASSMatrixmaxLikmemiscmiscToolsmsmmvtnormnlmenumDerivplmplotrixrbibutilsRcppRdpacksandwichsurvivalyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Doctoral Publications | Articles |
| Attituded toward working mothers | Attitudes |
| Bread for sandwiches | bread.Rchoice |
| Get average marginal effects for heterokedastic binary models and IV probit models | effect |
| Get average marginal effects for heterokedastic binary models | effect.hetprob print.effect.hetprob print.summary.effect.hetprob summary.effect.hetprob |
| Get average marginal effects for IV Probit model. | effect.ivpml print.effect.ivpml print.summary.effect.ivpml summary.effect.ivpml |
| Get the conditional individual coefficients | effect.Rchoice |
| Gradient for observations | estfun.Rchoice |
| Get Model Summaries for use with "mtable" for objects of class effect.hetprob | getSummary.effect.hetprob |
| Get Model Summaries for use with "mtable" for objects of class effect.ivpml | getSummary.effect.ivpml |
| Get Model Summaries for use with "mtable" for objects of class hetprob | getSummary.hetprob |
| Get Model Summaries for use with "mtable" for objects of class ivpml | getSummary.ivpml |
| Get Model Summaries for use with "mtable" for object of class Rchoice | getSummary.Rchoice |
| German Health Care Data | Health |
| Estimate heteroskedastic binary (Probit or Logit) model. | bread.hetprob coef.hetprob df.residual.hetprob estfun.hetprob hetprob logLik.hetprob model.matrix.hetprob predict.hetprob print.hetprob print.summary.hetprob summary.hetprob terms.hetprob vcov.hetprob |
| Estimate Instrumental Variable Probit model by Maximum Likelihood. | bread.ivpml coef.ivpml df.residual.ivpml estfun.ivpml ivpml logLik.ivpml model.matrix.ivpml predict.ivpml print.ivpml print.summary.ivpml summary.ivpml terms.ivpml vcov.ivpml |
| Plot the distribution of conditional expectation for random parameters. | plot.Rchoice |
| Estimate discrete choice model with random parameters | coef.Rchoice df.residual.Rchoice fitted.Rchoice logLik.Rchoice model.matrix.Rchoice ordinal print.Rchoice print.summary.Rchoice Rchoice residuals.Rchoice summary.Rchoice terms.Rchoice update.Rchoice |
| Model formula for Rchoice models | is.rFormula model.frame.rFormula model.matrix.rFormula rFormula |
| vcov method for Rchoice objects | cor.Rchoice cov.Rchoice se.cov.Rchoice vcov.Rchoice |
| Labor Force Participation | Workmroz |
