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BayesianPower  

Sample Size and Power for Comparing Inequality Constrained Hypotheses
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesianPower", "0.2.3")



Attach the package and use:
library("BayesianPower")
Maintained by
Fayette Klaassen
[Scholar Profile | Author Map]
First Published: 2019-05-31
Latest Update: 2020-06-22
Description:
A collection of methods to determine the required sample size for the evaluation of inequality constrained hypotheses by means of a Bayes factor. Alternatively, for a given sample size, the unconditional error probabilities or the expected conditional error probabilities can be determined. Additional material on the methods in this package is available in Klaassen, F., Hoijtink, H. & Gu, X. (2019) .
How to cite:
Fayette Klaassen (2019). BayesianPower: Sample Size and Power for Comparing Inequality Constrained Hypotheses. R package version 0.2.3, https://cran.r-project.org/web/packages/BayesianPower. Accessed 03 May. 2025.
Previous versions and publish date:
0.1.6 (2019-05-31 10:50), 0.2.0 (2020-06-09 18:00), 0.2.1 (2020-06-15 14:10), 0.2.2 (2020-06-16 14:20)
Other packages that cited BayesianPower R package
View BayesianPower citation profile
Other R packages that BayesianPower depends, imports, suggests or enhances
Complete documentation for BayesianPower
Functions, R codes and Examples using the BayesianPower R package
Some associated functions: bayes_error . bayes_power . bayes_sampsize . calc_bf . calc_fc . eval_const . samp_bf . samp_dist . 
Some associated R codes: power_sampsize.R . utils.R .  Full BayesianPower package functions and examples
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