1 code implementation • 10 Apr 2020 • Panagiotis Papastamoulis, Ioannis Ntzoufras
A well known identifiability issue in factor analytic models is the invariance with respect to orthogonal transformations.
Methodology Computation
1 code implementation • 2 Jun 2019 • Panagiotis Papastamoulis
The flexibility provided by overfitting mixture models yields a simple and efficient way in order to estimate the unknown number of clusters and model parameters by Markov chain Monte Carlo (MCMC) sampling.
Methodology Computation
1 code implementation • 17 Jan 2017 • Panagiotis Papastamoulis
For this purpose an overfitting mixture of factor analyzers is introduced, assuming that the number of factors is fixed.
Methodology
no code implementations • 22 Sep 2016 • Panagiotis Papastamoulis, Magnus Rattray
The BayesBinMix package offers a Bayesian framework for clustering binary data with or without missing values by fitting mixtures of multivariate Bernoulli distributions with an unknown number of components.
Computation
