Introduction | Method Overview | Required Packages | Example: Income Estimation Using Linear Regression | Example: Binary Outcome Using Logistic Regression | Example: LightGBM with Hyperparameter Tuning | Supported Models | References | Conclusion
Package: sae.projection 0.1.5
sae.projection: Small Area Estimation Using Model-Assisted Projection Method
Combines information from two independent surveys using a model-assisted projection method. Designed for survey sampling scenarios where a large sample collects only auxiliary information (Survey 1) and a smaller sample provides data on both variables of interest and auxiliary variables (Survey 2). Implements a working model to generate synthetic values of the variable of interest by fitting the model to Survey 2 data and predicting values for Survey 1 based on its auxiliary variables (Kim & Rao, 2012) <doi:10.1093/biomet/asr063>.
Authors:
sae.projection_0.1.5.tar.gz
sae.projection_0.1.5.zip(r-4.7-any)sae.projection_0.1.5.zip(r-4.6-any)sae.projection_0.1.5.zip(r-4.5-any)
sae.projection_0.1.5.tgz(r-4.6-any)sae.projection_0.1.5.tgz(r-4.5-any)
sae.projection_0.1.5.tar.gz(r-4.7-any)sae.projection_0.1.5.tar.gz(r-4.6-any)
sae.projection_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sae.projection/json (API)
| # Install 'sae.projection' in R: |
| install.packages('sae.projection', repos = c('https://ridsonap.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alfrzlp/sae.projection/issues
Last updated from:4ef20cd4ad. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 463 | ||
| source / vignettes | OK | 408 | ||
| linux-release | OK | 512 | ||
| macos-release | OK | 564 | ||
| macos-oldrel | OK | 466 | ||
| windows-devel | OK | 496 | ||
| windows-release | OK | 487 | ||
| windows-oldrel | OK | 490 | ||
| wasm-release | OK | 157 |
Exports:ma_projectionprojection_randomforest
Dependencies:backportsbase64encbonsaibroombslibcachemcaretclasscliclockcodetoolsconflictedcpp11data.tableDBIdiagramdialsDiceDesigndigestdoParalleldplyre1071evaluatefarverfastmapfontawesomeforeachfsfurrrfuturefuture.applyGauProgenericsggplot2globalsgluegowergtablehardhathighrhtmltoolsinferipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalbfgslifecyclelightgbmlistenvlubridatemagrittrMASSMatrixmemoisemimeminqamitoolsmixoptmodeldatamodelenvModelMetricsnlmennetnumDerivparallellyparsnippatchworkpillarpkgconfigplyrprettyunitspROCprodlimprogressrproxypurrrR6randomForestrangerRANNrappdirsRColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2rlangrmarkdownROSErpartrsamplerstudioapiS7sassscalessfdshapeslidersparsevctrssplitfngrSQUAREMstringistringrsurveysurvivaltailorthemistibbletidymodelstidyrtidyselecttimechangetimeDatetinytextunetzdbutf8vctrsviridisLitewarpwithrworkflowsworkflowsetsxfunyamlyardstick
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| df_svy_A | df_svy_A |
| df_svy_B | df_svy_B |
| df_svy22 | df_svy22 |
| df_svy23 | df_svy23 |
| Model-Assisted Projection Estimator | ma_projection |
| Projection Estimator with Random Forest Algorithm | projection_randomforest |