Package: causalSLSE 0.3-1
causalSLSE: Semiparametric Least Squares Inference for Causal Effects
Several causal effects are measured using least squares regressions and basis function approximations. Backward and forward selection methods based on different criteria are used to select the basis functions.
Authors:
causalSLSE_0.3-1.tar.gz
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causalSLSE_0.3-1.tgz(r-4.4-x86_64)causalSLSE_0.3-1.tgz(r-4.4-arm64)causalSLSE_0.3-1.tgz(r-4.3-x86_64)causalSLSE_0.3-1.tgz(r-4.3-arm64)
causalSLSE_0.3-1.tar.gz(r-4.5-noble)causalSLSE_0.3-1.tar.gz(r-4.4-noble)
causalSLSE_0.3-1.tgz(r-4.4-emscripten)causalSLSE_0.3-1.tgz(r-4.3-emscripten)
causalSLSE.pdf |causalSLSE.html✨
causalSLSE/json (API)
| # Install 'causalSLSE' in R: |
| install.packages('causalSLSE', repos = c('https://pchausse.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:6382f1709b. Checks:OK: 1 WARNING: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 13 2024 |
| R-4.5-win-x86_64 | WARNING | Nov 13 2024 |
| R-4.5-linux-x86_64 | WARNING | Nov 13 2024 |
| R-4.4-win-x86_64 | WARNING | Nov 13 2024 |
| R-4.4-mac-x86_64 | WARNING | Nov 13 2024 |
| R-4.4-mac-aarch64 | WARNING | Nov 13 2024 |
| R-4.3-win-x86_64 | WARNING | Nov 13 2024 |
| R-4.3-mac-x86_64 | WARNING | Nov 13 2024 |
| R-4.3-mac-aarch64 | WARNING | Nov 13 2024 |
Exports:as.modelcausalSLSEcausalSLSE.cslseFitcausalSLSE.cslseModelcausalSLSE.formulacslseModelestSLSEestSLSE.cslseModelextractllSplinesllSplines.cslseModelllSplines.slseModelplot.cslseFitplot.slseFitpredict.cslseFitpredict.slseFitprint.cslseprint.cslseFitprint.cslseModelprint.slseFitprint.slseKnotsprint.summary.cslseprint.summary.cslseFitprint.summary.slseFitselSLSEselSLSE.cslseModelslseKnotsslseModelsummary.cslsesummary.cslseFitsummary.slseFit
Dependencies:askpasscurlhttrjsonlitelatticemimeopensslR6sandwichsystexregzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Converter into Model Objects | as.model as.model.cslse as.model.cslseFit as.model.slseFit |
| Causal Effect Based on Semiparametric Least Squares Models | causalSLSE causalSLSE.cslseFit causalSLSE.cslseModel causalSLSE.formula |
| Semiparametric Least Squares Estimator Model | cslseModel slseModel |
| Least Squares Estimate of 'cslseModel' or 'slseModel' Objects | estSLSE estSLSE.cslseModel estSLSE.slseModel |
| 'extract' Method for 'cslse' Objects | extract,cslse-method extract.cslse |
| 'extract' Method for 'slseFit' Objects | extract,slseFit-method extract.slseFit |
| Local Linear Splines Generator for Model Objects | llSplines llSplines.cslseModel llSplines.slseModel |
| Lalonde Subsample of the National Supported Work Demonstration Data (NSW) | nsw |
| Plot of Predicted Outcome | plot.cslseFit plot.slseFit |
| Outcome Prediction | predict.cslseFit predict.slseFit |
| Print Methods | print.cslse print.cslseFit print.cslseModel print.slseFit print.slseKnots print.slseModel print.summary.cslse print.summary.cslseFit print.summary.slseFit |
| Knots Selection Method | selSLSE selSLSE.cslseModel selSLSE.slseModel |
| Simulated Data | simDat1 |
| Simulated Data | simDat2 |
| Simulated Data | simDat3 |
| Simulated Data. | simDat4 |
| Simulated Data | simDat5 |
| Knots Creator for Basis Functions | slseKnots |
| Summary Method for Fitted Models | summary.cslse summary.cslseFit summary.slseFit |
| Update Methods | update.cslseModel update.slseKnots update.slseModel |
