Title: Predictive Probability for a Continuous Response with an ANOVA
Description: A Bayesian approach to using
predictive probability in an ANOVA construct with a continuous normal response,
when threshold values must be obtained for the question of interest to be
evaluated as successful (Sieck and Christensen (2021) <doi:10.1002/qre.2802>).
The Bayesian Mission Mean (BMM) is used to evaluate a question
of interest (that is, a mean that randomly selects combination of factor levels
based on their probability of occurring instead of averaging over the factor
levels, as in the grand mean). Under this construct, in contrast to a Gibbs
sampler (or Metropolis-within-Gibbs sampler), a two-stage sampling method is
required. The nested sampler determines the conditional posterior distribution
of the model parameters, given Y, and the outside sampler determines the marginal
posterior distribution of Y (also commonly called the predictive distribution for Y).
This approach provides a sample from the joint posterior distribution of Y and
the model parameters, while also accounting for the threshold value that must be
obtained in order for the question of interest to be evaluated as successful.
Suggests: rjags, coda, knitr, devtools, rmarkdown, testthat (>= 3.0.0)
Author: Victoria Sieck [aut, cre] (<https://orcid.org/0000-0002-7169-7795>),

Title: Object-Oriented Data Structures for R
Description: This package furnishes R with a suite of object-oriented data structures: stack, queue, deque, max-heap, min-heap, binary search tree, and splay tree.
Packaged: Wed Jan  9 20:34:57 2008; jhughes

Packaged: Fri Jan 11 07:27:09 2008; jhughes

Packaged: Thu Mar 27 09:21:58 2008; jhughes

Title: Model-Based Clustering and Classification with the Multivariate
Author: Antonio Punzo, Angelo Mazza, Paul D. McNicholas
Description: Fits mixtures of multivariate contaminated normal distributions
(with eigen-decomposed scale matrices) via the expectation conditional-
maximization algorithm under a clustering or classification paradigm.