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ppmSuite (version 0.3.4)

A Collection of Models that Employ Product Partition Distributions as a Prior on Partitions

Description

Provides a suite of functions that fit models that use PPM type priors for partitions. Models include hierarchical Gaussian and probit ordinal models with a (covariate dependent) PPM. If a covariate dependent product partition model is selected, then all the options detailed in Page, G.L.; Quintana, F.A. (2018) are available. If covariate values are missing, then the approach detailed in Page, G.L.; Quintana, F.A.; Mueller, P (2020) is employed. Also included in the package is a function that fits a Gaussian likelihood spatial product partition model that is detailed in Page, G.L.; Quintana, F.A. (2016) , and multivariate PPM change point models that are detailed in Quinlan, J.J.; Page, G.L.; Castro, L.M. (2023) . In addition, a function that fits a univariate or bivariate functional data model that employs a PPM or a PPMx to cluster curves based on B-spline coefficients is provided.

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Version

Install

install.packages('ppmSuite')

Monthly Downloads

215

Version

0.3.4

License

GPL

Maintainer

Garritt L. Page

Last Published

July 16th, 2023

Functions in ppmSuite (0.3.4)

ccp_ppm

Function that fits a multivariate correlated product partition change point model
ordinal_ppmx

Function that fits ordinal probit model with a PPMx as a prior on partitions
scallops

Scallops data
gaussian_ppmx

Function that fits Gaussian PPMx model
curve_ppmx

Gaussian PPMx Model for Functional Realizations
sppm

Function that fits spatial product partition model with Gaussian likelihood
ozone

Ozone data
SIMCE

Standardized testing data in Chile
rppmx

Function generates random realizations from a PPM or PPMx
icp_ppm

Function that fits the multivariate independent product partition change point model
bear

Bear dataset