Search Results - subject:"Model based clustering"

Dimension reduction for model-based clustering via mixtures of multivariate <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$t$$</EquationSource> <EquationSource Format="M...

Morris, Katherine; McNicholas, Paul; Scrucca, Luca - In: Advances in Data Analysis and Classification 7 (2013) 3, pp. 321-338

We introduce a dimension reduction method for model-based clustering obtained from a finite mixture of <InlineEquation …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010995284

Dimension reduction for model-based clustering via mixtures of shifted asymmetric Laplace distributions

Morris, Katherine; McNicholas, Paul D. - In: Statistics & Probability Letters 83 (2013) 9, pp. 2088-2093

A dimension reduction method for model-based clustering via a finite mixture of shifted asymmetric Laplace …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010678721

Model-based clustering of high-dimensional data streams with online mixture of probabilistic PCA

Bellas, Anastasios; Bouveyron, Charles; Cottrell, Marie; … - In: Advances in Data Analysis and Classification 7 (2013) 3, pp. 281-300

Model-based clustering is a popular tool which is renowned for its probabilistic foundations and its flexibility …. However, model-based clustering techniques usually perform poorly when dealing with high-dimensional data streams, which are … nowadays a frequent data type. To overcome this limitation of model-based clustering, we propose an online inference algorithm …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010698271

On the distribution of posterior probabilities in finite mixture models with application in clustering

Melnykov, Volodymyr - In: Journal of Multivariate Analysis 122 (2013) C, pp. 175-189

The paper discusses an approach based on the multivariate Delta method for approximating the distribution of posterior probabilities in finite mixture models. It can be used for developing distributions of many other characteristics involving posterior probabilities such as the entropy of fuzzy...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010702811

Family firm types based on the professionalization construct : exploratory research

Dekker, Julie C.; Lybaert, Nadine; Steijvers, Tensie; … - In: Family business review : journal of the Family Firm … 26 (2013) 1, pp. 81-99

Persistent link: https://ebvufind01.dmz1.zbw.eu/10009754739

Forecasting simultaneously high-dimensional time series : a robust model-based clustering approach

Wang, Yongning; Tsay, Ruey S.; Ledolter, Johannes; … - In: Journal of forecasting 32 (2013) 8, pp. 673-684

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010344465

A Copula-Based Algorithm for Discovering Patterns of Dependent Observations

Lascio, F.; Giannerini, Simone - In: Journal of Classification 29 (2012) 1, pp. 50-75

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010848613

Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions

Ingrassia, Salvatore; Minotti, Simona; Vittadini, Giorgio - In: Journal of Classification 29 (2012) 3, pp. 363-401

Cluster-weighted modeling (CWM) is a mixture approach to modeling the joint probability of data coming from a heterogeneous population. Under Gaussian assumptions, we investigate statistical properties of CWM from both theoretical and numerical point of view; in particular, we show that Gaussian...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010848619

A Criterion Based on the Mahalanobis Distance for Cluster Analysis with Subsampling

Picard, Nicolas; Bar-Hen, Avner - In: Journal of Classification 29 (2012) 1, pp. 23-49

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010539473

Theoretical and practical considerations on the convergence properties of the Fisher-EM algorithm

Bouveyron, Charles; Brunet, Camille - In: Journal of Multivariate Analysis 109 (2012) C, pp. 29-41

The Fisher-EM algorithm has been recently proposed in Bouveyron and Brunet (2012) [5] for the simultaneous visualization and clustering of high-dimensional data. It is based on a latent mixture model which fits the data into a latent discriminative subspace with a low intrinsic dimension....

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010572288