Title: Cramer-von Mises Goodness-of-Fit Tests
Author: Romain Azais, Sandie Ferrigno and Marie-Jose Martinez
Description: It is devoted to Cramer-von Mises goodness-of-fit tests.
It implements three statistical methods based on Cramer-von Mises statistics to estimate and test a regression model.

Title: Cross-Validation for Model Selection
person("Ludvig Renbo", "Olsen", email = "r-pkgs@ludvigolsen.dk", role = c("aut", "cre")),
Description: Run cross-validation of one or multiple regression models and get relevant evaluation
metrics in a tidy format. Validate the best model on a test set and compare it to a baseline evaluation.
Currently supports Gaussian and binomial regression.
Described in chp. 5 of Jeyaraman, B., Olsen, L. R., & Wambugu M. (2019, ISBN: 9781838550134).
Imports: data.table (>= 1.12), dplyr, plyr, tidyr (>= 0.7.0), ggplot2,
2.2-1), broom, stringr, mltools (>= 0.3.5), rlang
Suggests: knitr, groupdata2 (>= 1.1), e1071, rmarkdown, testthat, AUC,
Packaged: 2019-07-01 13:26:16 UTC; ludvigolsen
Maintainer: Ludvig Renbo Olsen <r-pkgs@ludvigolsen.dk>

Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R., & Wambugu M. (2019, ISBN: 9781838550134).
Suggests: knitr, groupdata2 (>= 1.1.1), e1071, rmarkdown, testthat,
Packaged: 2019-07-20 13:32:15 UTC; ludvigolsen

person("Benjamin Hugh", "Zachariae", role = "aut")
Description: Cross-validate one or multiple regression models and get relevant evaluation
Packaged: 2019-08-05 14:19:21 UTC; ludvigolsen

Alternatively, evaluate predictions from an external model.
Currently supports linear regression, logistic regression and
(some functions only) multiclass classification.
2.2-1), broom, stringr, mltools (>= 0.3.5), rlang, utils
Packaged: 2019-09-05 19:21:31 UTC; ludvigolsen

Description: Cross-validate one or multiple regression and classification models
and get relevant evaluation metrics in a tidy format. Validate the
best model on a test set and compare it to a baseline evaluation.
Alternatively, evaluate predictions from an external model. Currently
supports regression and classification (binary and multiclass).
Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R.,
Imports: data.table (>= 1.12), dplyr, plyr, tidyr (>= 0.8.3), ggplot2,
stringr, mltools (>= 0.3.5), rlang, utils, lifecycle
Suggests: knitr, groupdata2 (>= 1.1.2), e1071 (>= 1.7-2), rmarkdown,
testthat (>= 2.2.1), AUC, furrr, ModelMetrics (>= 1.2.2), covr
Packaged: 2019-09-28 23:19:24 UTC; ludvigolsen