Package: cv 2.0.3
Georges Monette
cv: Cross-Validating Regression Models
Cross-validation methods of regression models that exploit features of various modeling functions to improve speed. Some of the methods implemented in the package are novel, as described in the package vignettes; for general introductions to cross-validation, see, for example, Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani (2021, ISBN 978-1-0716-1417-4, Secs. 5.1, 5.3), "An Introduction to Statistical Learning with Applications in R, Second Edition", and Trevor Hastie, Robert Tibshirani, and Jerome Friedman (2009, ISBN 978-0-387-84857-0, Sec. 7.10), "The Elements of Statistical Learning, Second Edition".
Authors:
cv_2.0.3.tar.gz
cv_2.0.3.zip(r-4.5)cv_2.0.3.zip(r-4.4)cv_2.0.3.zip(r-4.3)
cv_2.0.3.tgz(r-4.4-any)cv_2.0.3.tgz(r-4.3-any)
cv_2.0.3.tar.gz(r-4.5-noble)cv_2.0.3.tar.gz(r-4.4-noble)
cv_2.0.3.tgz(r-4.4-emscripten)cv_2.0.3.tgz(r-4.3-emscripten)
cv.pdf |cv.html✨
cv/json (API)
NEWS
# Install 'cv' in R: |
install.packages('cv', repos = c('https://gmonette.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gmonette/cv/issues
- Pigs - Body Weights of 48 Pigs in 9 Successive Weeks
Last updated 1 months agofrom:2c1eedd4ca. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 15 2024 |
R-4.5-win | OK | Nov 15 2024 |
R-4.5-linux | OK | Nov 15 2024 |
R-4.4-win | OK | Nov 15 2024 |
R-4.4-mac | OK | Nov 15 2024 |
R-4.3-win | OK | Nov 15 2024 |
R-4.3-mac | OK | Nov 15 2024 |
Exports:BayesRuleBayesRule2compareFoldscvcvComputecvInfocvMixedcvSelectfoldfoldsGetResponsemedAbsErrmodelsmsermseselectModelListselectStepAICselectTransselectTransStepAIC
Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11DerivdoBydoParalleldplyrfansifarverforeachFormulagenericsggplot2glmmTMBgluegtablegtoolsinsightisobanditeratorslabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectTMButf8vctrsviridisLitewithr
Computational and technical notes on cross-validating regression models
Rendered fromcv-notes.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-09-02
Started: 2024-04-03
Cross-validating mixed-effects models
Rendered fromcv-mixed.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-09-02
Started: 2024-04-03
Cross-validating model selection
Rendered fromcv-selection.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-09-15
Started: 2024-04-03
Cross-validating regression models
Rendered fromcv.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-09-04
Started: 2023-08-03
Extending the cv package
Rendered fromcv-extend.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-09-05
Started: 2023-08-25
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Cross-Validate Regression Models | as.data.frame.cv as.data.frame.cvList cv cv.default cv.glm cv.lm cv.rlm cvInfo cvInfo.cv cvInfo.cvList cvInfo.cvModList plot.cv plot.cvList print.cv print.cvDataFrame print.cvList summary.cv summary.cvDataFrame summary.cvList |
Cross-Validate a Model-Selection Procedure | coef.cvSelect compareFolds cv.function cvInfo.cvSelect selectModelList selectStepAIC selectTrans selectTransStepAIC |
Cross-Validate Mixed-Effects Model | cv.glmmTMB cv.lme cv.merMod |
Cross-Validate Several Models Fit to the Same Data | as.data.frame.cvModList cv.modList models plot.cvModList print.cvModList summary.cvModList |
Utility Functions for the cv Package | cvCompute cvMixed cvSelect fold fold.folds folds GetResponse GetResponse.default GetResponse.glmmTMB GetResponse.lme GetResponse.merMod GetResponse.modList print.folds |
Cost Functions for Fitted Regression Models | BayesRule BayesRule2 costFunctions medAbsErr mse rmse |
Body Weights of 48 Pigs in 9 Successive Weeks | Pigs |