Families of Parsimonious Finite Mixtures of Regression Models
نویسندگان
چکیده
Finite mixtures of regression models offer a flexible framework for investigating heterogeneity in data with functional dependencies. These models can be conveniently used for unsupervised learning on data with clear regression relationships. We extend such models by imposing an eigen-decomposition on the multivariate error covariance matrix. By constraining parts of this decomposition, we obtain families of parsimonious mixtures of regressions and mixtures of regressions with concomitant variables. These families of models account for correlations between multiple responses. An expectation-maximization algorithm is presented for parameter estimation and performance is illustrated on simulated and real data.
منابع مشابه
Finite mixtures of generalized linear regression models
Generalized linear models have become a standard technique in the statistical modelling toolbox for investigating relationships between variables. The assumption of homogeneity of regression coefficients over all observations can be relaxed by incorporating generalized linear models into the finite mixture framework. The model class consisting of finite mixtures of generalized linear models is ...
متن کاملDetermination of the genetic and non-genetic variations in growth curve of Zandi lambs by random regression models
The aim of this study was to model the variances and covariances of body weight in Zandi sheep from 60 to 365 days of age using random regression models (RRM). Legendre polynomials of different orders were used to model the direct and maternal covariances. Mean trends were also modeled through a quadratic regression on orthogonal polynomials of age. Homogeneity and heterogeneity of the residual...
متن کاملDirichlet Process Parsimonious Mixtures for clustering
The parsimonious Gaussian mixture models, which exploit an eigenvalue decomposition of the group covariance matrices of the Gaussian mixture, have shown their success in particular in cluster analysis. Their estimation is in general performed by maximum likelihood estimation and has also been considered from a parametric Bayesian prospective. We propose new Dirichlet Process Parsimonious mixtur...
متن کاملApplications of finite mixtures of regression models
Package flexmix provides functionality for fitting finite mixtures of regression models. The available model class includes generalized linear models with varying and fixed effects for the component specific models and multinomial logit models for the concomitant variable models. This model class includes random intercept models where the random part is modelled by a finite mixture instead of a...
متن کاملParsimonious Gaussian mixture models
Parsimonious Gaussian mixture models are developed using a latent Gaussian model which is closely related to the factor analysis model. These models provide a unified modeling framework which includes the mixtures of probabilistic principal component analyzers and mixtures of factor of analyzers models as special cases. In particular, a class of eight parsimonious Gaussian mixture models which ...
متن کامل