Package: gWQS 3.0.5

gWQS: Generalized Weighted Quantile Sum Regression

Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) <doi:10.1007/s13253-014-0180-3>), a random subset implementation of WQS (Curtin et al. (2019) <doi:10.1080/03610918.2019.1577971>), a repeated holdout validation WQS (Tanner et al. (2019) <doi:10.1016/j.mex.2019.11.008>) and a WQS with 2 indices (Renzetti et al. (2023) <doi:10.3389/fpubh.2023.1289579>) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.

Authors:Stefano Renzetti [aut, cre], Paul Curtin [aut], Allan C Just [ctb], Ghalib Bello [ctb], Chris Gennings [aut]

gWQS_3.0.5.tar.gz
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gWQS_3.0.5.tgz(r-4.4-any)gWQS_3.0.5.tgz(r-4.3-any)
gWQS_3.0.5.tar.gz(r-4.5-noble)gWQS_3.0.5.tar.gz(r-4.4-noble)
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gWQS.pdf |gWQS.html✨
gWQS/json (API)

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13 exports 7 stars 2.42 score 109 dependencies 2 dependents 7 mentions 40 scripts 903 downloads

Last updated 10 months agofrom:c189db1b18. Checks:OK: 7. Indexed: yes.

Exports:gwqsgwqs_barplotgwqs_boxplotgwqs_fitted_vs_residgwqs_levels_scatterplotgwqs_multinomgwqs_rankgwqs_ROCgwqs_scatterplotgwqs_summary_tabgwqs_weights_tabgwqsrhselectdatavars

Dependencies:abindbackportsbase64encbookdownbootbroombslibcachemcarcarDataclicodetoolscolorspacecommonmarkcowplotcpp11crayondata.tableDerivdigestdoBydplyrevaluatefansifarverfastmapfontawesomefsfuturefuture.applygenericsggplot2ggrepelglobalsgluegridSVGgtablehighrhtmltoolshttpuvisobandjquerylibjsonlitekableExtraknitrlabelinglaterlatticelifecyclelistenvlme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellnlmenloptrnnetnumDerivparallellypbkrtestpillarpkgconfigplotROCplyrpromisespsclpurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrlistrmarkdownrstudioapisassscalesshinysourcetoolsSparseMstringistringrsurvivalsvglitesystemfontstibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunXMLxml2xtableyaml