A factor mixture analysis model for multivariate binary data

Details A factor mixture analysis model for multivariate binary data A factor mixture analysis model for multivariate binary data

2010-10-12

arxiv.org/abs/1010.2314v1

Statistics

Methodology

27 pages, 2 figures

Scientific paper

The paper proposes a latent variable model for binary data coming from an unobserved heterogeneous population. The heterogeneity is taken into account by replacing the traditional assumption of Gaussian distributed factors by a finite mixture of multivariate Gaussians. The aim of the proposed model is twofold: it allows to achieve dimension reduction when the data are dichotomous and, simultaneously, it performs model based clustering in the latent space. Model estimation is obtained by means of a maximum likelihood method via a generalized version of the EM algorithm. In order to evaluate the performance of the model a simulation study and two real applications are illustrated.

Affiliated with

Also associated with

No associations

Rating

A factor mixture analysis model for multivariate binary data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A factor mixture analysis model for multivariate binary data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A factor mixture analysis model for multivariate binary data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-608164