On the occasional exactness of the distributional transform approximation for direct Gaussian copula models with discrete margins

The direct Gaussian copula model with discrete margins is appealing but poses computational challenges due to its intractable likelihood. We show that the distributional transform-based approximate likelihood is essentially exact for some variants of the model, and we propose a quantity that can be used to assess exactness for a given dataset.

Files

Metadata

Work Title On the occasional exactness of the distributional transform approximation for direct Gaussian copula models with discrete margins
Access
Open Access
Creators
  1. John Hughes
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Statistics and Probability Letters
Publication Date October 1, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1016/j.spl.2021.109159
Deposited July 15, 2021

Versions

Analytics

Collections

This resource is currently not in any collection.

Work History

Version 1
published

  • Created
  • Added DT_exact_Hughes.pdf
  • Added Creator John Hughes
  • Published
  • Updated
  • Updated
  • Updated