bear

Number of physiological measurements from 54 bears.

datasets

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)
<doi:10.1007/s11222-017-9777-z> are available. If covariate values are missing,
then the approach detailed in Page, G.L.; Quintana, F.A.; Mueller, P (2020)
<doi:10.1080/10618600.2021.1999824> 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) <doi:10.1214/15-BA971>, and
multivariate PPM change point models that are detailed in Quinlan, J.J.; Page, G.L.;
Castro, L.M. (2023) <doi:10.1214/22-BA1344>. 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.

Garritt L. Page

ppmSuite

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

Jose J. Quinlan

S. McKay Curtis

Radford M. Neal

bear function

data: A data frame with 54 rows and the following 9 variables:<dl>
 <dt>age</dt>
<dd></dd> <dt>length</dt>
<dd></dd> <dt>sex</dt>
<dd></dd> <dt>weight</dt>
<dd></dd> <dt>chest</dt>
<dd></dd> <dt>headlength</dt>
<dd></dd> <dt>headwid</dt>
<dd></dd> <dt>month</dt>
<dd></dd> <dt>neck</dt>
<dd></dd>
</dl>

Format

Bear dataset — bear

data: A data frame with 54 rows and the following 9 variables:<dl>
 <dt>age</dt>
<dd></dd>

 <dt>length</dt>
<dd></dd>

 <dt>sex</dt>
<dd></dd>

 <dt>weight</dt>
<dd></dd>

 <dt>chest</dt>
<dd></dd>

 <dt>headlength</dt>
<dd></dd>

 <dt>headwid</dt>
<dd></dd>

 <dt>month</dt>
<dd></dd>

 <dt>neck</dt>
<dd></dd>


</dl>

bear: Bear dataset

Description

Arguments

Format