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PRP  

Bayesian Prior and Posterior Predictive Replication Assessment
View on CRAN: Click here


Download and install PRP package within the R console
Install from CRAN:
install.packages("PRP")

Install from Github:
library("remotes")
install_github("cran/PRP")

Install by package version:
library("remotes")
install_version("PRP", "0.1.1")



Attach the package and use:
library("PRP")
Maintained by
Yi Zhao
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-12-13
Latest Update: 2021-12-13
Description:
Utilize the Bayesian prior and posterior predictive checking approach to provide a statistical assessment of replication success and failure. The package is based on the methods proposed in Zhao,Y., Wen X.(2021) .
How to cite:
Yi Zhao (2021). PRP: Bayesian Prior and Posterior Predictive Replication Assessment. R package version 0.1.1, https://cran.r-project.org/web/packages/PRP. Accessed 05 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited PRP R package
View PRP citation profile
Other R packages that PRP depends, imports, suggests or enhances
Complete documentation for PRP
Functions, R codes and Examples using the PRP R package
Some associated functions: Q . RPP_filtered . egger . mortality . posterior_prp . prior_prp . prob_to_r . severity . 
Some associated R codes: Q.R . egger.R . mortality.R . posterior_prp.R . prior_prp.R . probability.R . rpp_filtered.R . severity.R .  Full PRP package functions and examples
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