dcut

This function computes the value of the
probability density function for the cut-points. The
distribution is induced by a Dirichlet distribution
on the prior probabilities of the response.

Implements the pseudo-R2D2 prior for ordinal regression from the paper "Psuedo-R2D2 prior for high-dimensional ordinal regression" by Yanchenko (2025) <doi:10.48550/arXiv.2502.17491>. In particular, it provides code to evaluate the probability distribution function for the cut-points, compute the log-likelihood, calculate the hyper-parameters for the global variance parameter, find the distribution of McFadden's coefficient-of-determination, and fit the model in 'rstan'. Please cite the paper if you use these codes.

Eric Yanchenko

R2D2ordinal

Implements Pseudo-R2D2 Prior for Ordinal Regression

dcut function

<dl><dt>tau</dt>
<dd>cut-points</dd>
<dt>W</dt>
<dd>global variance</dd>
<dt>alpha</dt>
<dd>concentration parameters for prior probabilities of Y</dd>
<dt>log</dt>
<dd>logical; if TRUE, returns log pdf</dd></dl>

Arguments

PDF of cut-points — dcut

<dl>

<dt>tau</dt>
<dd>cut-points</dd>


<dt>W</dt>
<dd>global variance</dd>


<dt>alpha</dt>
<dd>concentration parameters for prior probabilities of Y</dd>


<dt>log</dt>
<dd>logical; if TRUE, returns log pdf</dd>

</dl>

dcut: PDF of cut-points

Description

Usage

Value

Arguments

Examples