Efficient Bayesian analysis of multivariate aggregate choices

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5 Citations (Scopus)


In estimating individual choice behaviour using multivariate aggregate choice data, the method of data augmentation requires the imputation of individual choices given their partial sums. This article proposes and develops an efficient procedure of simulating multivariate individual choices given their aggregate sums, capitalizing on a sequence of auxiliary distributions. In this framework, a joint distribution of multiple binary vectors given their sums is approximated as a sequence of conditional Bernoulli distributions. The proposed approach is evaluated through a simulation study and is applied to a political science study.

Original languageEnglish
Pages (from-to)3352-3366
Number of pages15
JournalJournal of Statistical Computation and Simulation
Issue number16
Publication statusPublished - 2015 Nov 2

Bibliographical note

Funding Information:
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0011866).

Publisher Copyright:
© 2014 Taylor & Francis.

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


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