Package: ipd 0.1.4
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Stephen Salerno
ipd: Inference on Predicted Data
Performs valid statistical inference on predicted data (IPD) using recent methods, where for a subset of the data, the outcomes have been predicted by an algorithm. Provides a wrapper function with specified defaults for the type of model and method to be used for estimation and inference. Further provides methods for tidying and summarizing results. Salerno et al., (2024) <doi:10.48550/arXiv.2410.09665>.
Authors:
ipd_0.1.4.tar.gz
ipd_0.1.4.zip(r-4.5)ipd_0.1.4.zip(r-4.4)ipd_0.1.4.zip(r-4.3)
ipd_0.1.4.tgz(r-4.5-any)ipd_0.1.4.tgz(r-4.4-any)ipd_0.1.4.tgz(r-4.3-any)
ipd_0.1.4.tar.gz(r-4.5-noble)ipd_0.1.4.tar.gz(r-4.4-noble)
ipd_0.1.4.tgz(r-4.4-emscripten)ipd_0.1.4.tgz(r-4.3-emscripten)
ipd.pdf |ipd.html✨
ipd/json (API)
NEWS
# Install 'ipd' in R: |
install.packages('ipd', repos = c('https://ipd-tools.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ipd-tools/ipd/issues
Pkgdown site:https://ipd-tools.github.io
Last updated 1 months agofrom:e92205859a. Checks:5 OK, 3 NOTE. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Feb 05 2025 |
R-4.5-win | NOTE | Feb 05 2025 |
R-4.5-mac | NOTE | Feb 05 2025 |
R-4.5-linux | NOTE | Feb 05 2025 |
R-4.4-win | OK | Feb 05 2025 |
R-4.4-mac | OK | Feb 05 2025 |
R-4.3-win | OK | Feb 05 2025 |
R-4.3-mac | OK | Feb 05 2025 |
Exports:Aaugmentcalc_lhat_glmcompute_cdfcompute_cdf_diffest_iniglanceipdlink_gradlink_Hessianlog1pexplogistic_get_statsmean_psimean_psi_popolsols_get_statsoptim_estoptim_weightspostpi_analytic_olspostpi_boot_logisticpostpi_boot_olsppi_logisticppi_meanppi_olsppi_plusplus_logisticppi_plusplus_logistic_estppi_plusplus_meanppi_plusplus_mean_estppi_plusplus_olsppi_plusplus_ols_estppi_plusplus_quantileppi_plusplus_quantile_estppi_quantilepsipspa_logisticpspa_meanpspa_olspspa_poissonpspa_quantilepspa_yrectified_cdfrectified_p_valueSigma_calsim_data_ysimdattidywlszconfint_genericzstat_generic
Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygamgenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6randomForestrangerRColorBrewerRcppRcppEigenrecipesreshape2rlangrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr