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predRupdate
View on CRAN: Click
here
Download and install predRupdate package within the R console
Install from CRAN:
install.packages("predRupdate")
Install from Github:
library("remotes")
install_github("cran/predRupdate") Install by package version:
library("remotes")
install_version("predRupdate", "0.2.1") Attach the package and use:
library("predRupdate")
Maintained by
Glen P. Martin
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All associated links for this package
First Published: 2023-04-27
Latest Update: 2025-07-02
Description:
Evaluate the predictive performance of an existing (i.e. previously
developed) prediction/ prognostic model given relevant information about the
existing prediction model (e.g. coefficients) and a new dataset. Provides a
range of model updating methods that help tailor the existing model to the
new dataset; see Su et al. (2018) . Techniques
to aggregate multiple existing prediction models on the new data are also
provided; see Debray et al. (2014) and Martin et al.
(2018) ).
How to cite:
Glen P. Martin (2023). predRupdate: Prediction Model Validation and Updating. R package version 0.2.1, https://cran.r-project.org/web/packages/predRupdate. Accessed 04 Aug. 2026.
Previous versions and publish date:
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Complete documentation for predRupdate
Functions, R codes and Examples using
the predRupdate R package
Some associated functions: SYNPM . dummy_vars . inv_logit . logit . map_newdata . predRupdate-package . pred_input_info . pred_predict . pred_stacked_regression . pred_update . pred_validate .
Some associated R codes: data.R . flex_calplot.R . map_newdata.R . predRupdate-package.R . pred_input_info.R . pred_input_info_input_checks.R . pred_predict.R . pred_stacked_regression.R . pred_update.R . pred_validate.R . utils.R . validate_logistic.R . validate_survival.R . Full predRupdate package functions and examples
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