Package: InvStablePrior 0.1.0

InvStablePrior: Inverse Stable Prior for Widely-Used Exponential Models

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.

Authors:Dexter Cahoy [aut, cre], Joseph Sedransk [aut]

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Peer review:

Bug tracker:https://github.com/dcahoy/invstableprior/issues

On CRAN:

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Last updated 2 years agofrom:6e7e9a1a8e. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:isdexpisexpishalfnisinvgamispoi

Dependencies:clicodacpp11fdrtoolglueigraphlatticelifecyclemagrittrMatrixnimblenumDerivpkgconfigpracmaR6rlangvctrs