A new regression model for bounded multivariate responses

AGNESE MARIA DI BRISCO, R Ascari, S Migliorati, A Ongaro

Research output: Contribution to conferencePaperpeer-review

Abstract

The aim of this work is to propose a new multivariate regression model for compositional data, i.e., vectors of proportions. It is based on a mixture of Dirichletdistributed components and it enables many relevant properties for compositional data as well as accounting for positive correlations. Despite the complexity of the model, its special mixture structure provides a greater flexibility and a richer parameterization than the standard Dirichlet regression (DirReg) model and, moreover, guarantees its identifiability. We illustrate the performance and the goodness of fit of our new model through an application to the last Italian elections data.
Original languageEnglish
Pages817-822
Number of pages6
Publication statusPublished - 2019
EventSmart Statistics for Smart Applications - SIS 2019 - Milano, Italy
Duration: 1 Jan 2019 → …

Conference

ConferenceSmart Statistics for Smart Applications - SIS 2019
CityMilano, Italy
Period1/01/19 → …

Keywords

  • bayesian inference
  • dirichlet distribution
  • mixture model
  • simplex

Fingerprint

Dive into the research topics of 'A new regression model for bounded multivariate responses'. Together they form a unique fingerprint.

Cite this