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TKApprox  

A General Framework for Bayesian Estimation Using the 'Tierney'-'Kadane' Approximation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("TKApprox", "0.1.0")



Attach the package and use:
library("TKApprox")
Maintained by
Shikhar Tyagi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-07
Latest Update: 2026-08-07
Description:
Provides a distribution-independent framework for Bayesian estimation of arbitrary univariate probability models using the 'Tierney'-'Kadane' approximation ('Tierney' & 'Kadane', 1986 <doi:10.1080/01621459.1986.10478240>). Users specify the probability distribution, likelihood, prior distributions, and censoring mechanism, while the package automatically constructs the posterior distribution, computes posterior modes and Hessian matrices, approximates posterior expectations under several Bayesian loss functions, and returns Bayesian parameter estimates, posterior covariance matrices, credible intervals, diagnostic plots, and model comparison statistics. Supports complete, right-, left-, interval-, Type-I, Type-II, progressive Type-II, hybrid, and doubly censored data ('Lawless', 2003 <ISBN:978-0-471-37215-8>; 'Meeker' & 'Escobar', 1998 <ISBN:978-0-471-14328-4>; 'Balakrishnan' & 'Aggarwala', 2000 <ISBN:978-0-8176-4129-0>; 'Kundu' & 'Pradhan', 2009 <doi:10.1198/TECH.2009.0019>), making it a flexible tool for Bayesian reliability, survival, and lifetime data analysis.
How to cite:
Shikhar Tyagi (2026). TKApprox: A General Framework for Bayesian Estimation Using the 'Tierney'-'Kadane' Approximation. R package version 0.1.0, https://cran.r-project.org/web/packages/TKApprox. Accessed 24 Oct. 2026.
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Complete documentation for TKApprox
Functions, R codes and Examples using the TKApprox R package
Full TKApprox package functions and examples
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