Archive for the ‘Journal’ Category

How Many Clusters? Which Clustering Method? Answers via Model-Based Cluster Analysis

Monday, March 2nd, 2009

Title: How Many Clusters? Which Clustering Method? Answers via Model-Based Cluster Analysis PRINTED

Author: Fraley, C; Raftery, AE

Source: COMPUTER JOURNAL,vol.41,no.8,pp.578-588,1998

Keywords: SPATIAL POINT-PROCESSES; EM ALGORITHM; MATHEMATICAL MORPHOLOGY; MAXIMUM-LIKELIHOOD; PRINCIPAL CURVES; FEATURES; CLASSIFICATION; CONVERGENCE; NETWORKS; MIXTURES

 

(RefWorks Listed; DL; PT)

Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood

Monday, March 2nd, 2009

Title: Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood

Author: Biernacki, C; Celeux, G; Govaert, G

Source: Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 22, no. 7, pp. 719 - 725, July 2000

Keywords: Mixture model, clustering, integrated likelihood, BIC, integrated completed likelihood, ICL criterion

 

(RefWorks Listed; DL)

The EM algorithm - An Old Folk-Song Sung to a Fast New Tune

Monday, March 2nd, 2009

Title: The EM algorithm - An Old Folk-Song Sung to a Fast New Tune

Author: Meng, XL; vanDyk, D

Source: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, vol.59, no.3, pp.511-540, 1997

Keywords:  data augmentation; expectation conditional maximization algorithm; expectation conditional maximization either algorithm; Gibbs sampler; incomplete data; Markov chain Monte Carlo method; missing data; model reduction; multivariate t-distributions; Poisson model; positron emission tomography; rate of convergence; sage algorithm

 

(RefWorks Listed; DL)

Maximum Likelihood Estimation via the ECM Algorithm A general Framework

Monday, March 2nd, 2009

Title: Maximum Likelihood Estimation via the ECM Algorithm: A general Framework

Author: Meng, XL; Rubin, DB

Source: BIOMETRIKA,vol.80,no.2,pp.267-278,1993

Some Key Words: Baycsian inference; Conditional maximization; Constrained optimization; EM algorithm; Gibbs sampler; Incomplete data; Iterated conditional modes; Iterative proportional fitting; Missing data

 

(RefWorks Listed; DL)

Optimization transfer using surrogate objective functions - Rejoinder

Monday, March 2nd, 2009

Title: Optimization transfer using surrogate objective functions - Rejoinder

Author: Hunter, DL; Lange, K

Source: Journal of computational and graphical statistics 9, 52-59. (2000)

 

(RefWorks Listed; DL)

Mixtures of Probabilistic Principal Component Analyzers

Monday, March 2nd, 2009

Title: Mixtures of Probabilistic Principal Component Analyzers

Author: Tipping, ME; Bishop CM

Source: Neural Computation 11(2), 443-482

 

(Refworks Listed; DL)

Parsimonious Gaussian Mixture Models

Monday, March 2nd, 2009

Title: Parsimonious Gaussian mixture models

Author: McNicholas, PD; Murphy, TB

Source: STATISTICS AND COMPUTING,vol.18,no.3,pp.285-296,2008

Keywords: Mixture models; Factor analysis; Probabilistic principal components analysis; Cluster analysis; Model-based clustering

 

(RefWorks Listed; DL; PT)

The EM Algorithm for Mixtures of Factor Analyzers

Monday, March 2nd, 2009

Title: The EM Algorithm for Mixtures of Factor Analyzers

Author: Ghahramani, Z; Hinton, GE

Source: Technical Report CRG-TR-96-1, University of Toronto, Toronto

 

(DL)

MCLUST: Software for Model-Based Clustering Density Estimation and Discriminant Analysis

Monday, March 2nd, 2009

Title: MCLUST: Software for Model-Based Clustering, Density Estimation, and Discriminant Analysis

Author: Fraley, C; Raftery, AE

Technical Report No. 415, University of Washington, Department of Statistics, 2002-2003

 

(DL)

MCLUST: Software for Model-Based Cluster Analysis

Monday, March 2nd, 2009

Title: MCLUST: Software for model-based cluster analysis

Author: Fraley, C; Raftery, AE

Source: JOURNAL OF CLASSIFICATION,vol.16,no.2,pp.297-306,1999

 

(RefWorks listed; DL)