Inverse Stable Prior for Widely-Used Exponential Models R package InvStablePrior version 0.1.1 Contains functions that allow Bayesian inference on a parameter of some widely-used exponential models. The functions can generate independent samples from the closed-form posterior distribution using the inverse stable prior. Inverse stable is a non-conjugate prior for a parameter of an exponential subclass of discrete and continuous data distributions (e.g. Poisson, exponential, inverse gamma, double exponential (Laplace), half-normal/half-Gaussian, etc.). The prior class provides flexibility in capturing a wide array of prior beliefs (right-skewed and left-skewed) as modulated by a parameter that is bounded in (0,1). The generated samples can be used to simulate the prior and posterior predictive distributions. More details can be found in Cahoy and Sedransk (2019) <doi:10.1007/s42519-018-0027-2>. The package can also be used as a teaching demo for introductory Bayesian courses. Software Imports: stats, fdrtool, nimble Dexter Cahoy <dexter.cahoy@gmail.com> Comprehensive R Archive Network (CRAN) Dexter Cahoy [aut, cre], Joseph Sedransk [aut] GPL (>= 3) 2023-08-21 application/tgz https://CRAN.R-project.org/package=InvStablePrior doi:10.32614/CRAN.package.InvStablePrior