# A new specification of generalized linear models for categorical data

arXiv: https://arxiv.org/abs/1404.7331 · HTML: https://mlsanity.com/paper/1404.7331/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2014.

## Built on by (most cited first, 1 of 1)

- [Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training](https://mlsanity.com/paper/2402.01238/) (2024)

## Abstract (arXiv)

Regression models for categorical data are specified in heterogeneous ways. We propose to unify the specification of such models. This allows us to define the family of reference models for nominal data. We introduce the notion of reversible models for ordinal data that distinguishes adjacent and cumulative models from sequential ones. The combination of the proposed specification with the definition of reference and reversible models and various invariance properties leads to a new view of regression models for categorical data.