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Bayesrel  

Bayesian Reliability Estimation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("Bayesrel", "0.7.8")



Attach the package and use:
library("Bayesrel")
Maintained by
Julius M. Pfadt
[Scholar Profile | Author Map]
First Published: 2019-01-20
Latest Update: 2023-08-09
Description:
Functionality for reliability estimates. For 'unidimensional' tests: Coefficient alpha, 'Guttman's' lambda-2/-4/-6, the Greatest lower bound and coefficient omega_u ('unidimensional') in a Bayesian and a frequentist version. For multidimensional tests: omega_t (total) and omega_h (hierarchical). The results include confidence and credible intervals, the probability of a coefficient being larger than a cutoff, and a check for the factor models, necessary for the omega coefficients. The method for the Bayesian 'unidimensional' estimates, except for omega_u, is sampling from the posterior inverse 'Wishart' for the covariance matrix based measures (see 'Murphy', 2007, . The Bayesian omegas (u, t, and h) are obtained by 'Gibbs' sampling from the conditional posterior distributions of (1) the single factor model, (2) the second-order factor model, (3) the bi-factor model, (4) the correlated factor model ('Lee', 2007, ).
How to cite:
Julius M. Pfadt (2019). Bayesrel: Bayesian Reliability Estimation. R package version 0.7.8, https://cran.r-project.org/web/packages/Bayesrel. Accessed 03 May. 2025.
Previous versions and publish date:
0.1.0 (2019-01-20 17:40), 0.6.1 (2020-03-04 17:10), 0.7.0.2 (2020-11-18 09:50), 0.7.0.3 (2021-01-07 14:00), 0.7.0.7 (2021-03-29 15:22), 0.7.0 (2020-11-11 13:20), 0.7.1 (2021-09-13 17:30), 0.7.4.1 (2022-04-06 22:22), 0.7.4.2 (2022-06-27 17:00), 0.7.4.3 (2022-08-10 18:00), 0.7.4.4 (2022-10-26 13:37), 0.7.4 (2022-02-10 18:10), 0.7.5 (2022-11-19 13:40), 0.7.7 (2023-08-09 17:40)
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Complete documentation for Bayesrel
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