Model‐based clustering of regression time series data via APECM—an AECM algorithm sung to an even faster beat

No abstract is available for this paper.

• Publication year

  2011

• Venue

  Statistical analysis and data mining

• Publication date

  2011-12-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1002/sam.10143
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Finite mixture models and model-based clustering

  2010cited by this paper
• Initializing Partition-Optimization Algorithms

  2009cited by this paper
• Finite Mixture Models

  2008cited by this paper
• The Practice of Cluster Analysis

  2006cited by this paper
• Nonparametric Clustering Techniques

  2006cited by this paper
• Generalized Least Squares

  2005influential reference
• On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures

  2003cited by this paper
• Model-Based Clustering, Discriminant Analysis, and Density Estimation

  2002cited by this paper
• Cluster Analysis

  2002cited by this paper
• Mixed-Effects Models in S and S-Plus

  2001cited by this paper
• The Art of Data Augmentation

  2001cited by this paper
• Finite Mixture Models

  2000cited by this paper
• On a mixture autoregressive model

  2000cited by this paper
• A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants

  1998cited by this paper
• The EM Algorithm—an Old Folk‐song Sung to a Fast New Tune

  1997influential reference
• Market Segmentation: Conceptual and Methodological Foundations

  1997cited by this paper
• The EM algorithm and extensions

  1996cited by this paper
• Approximate single linkage cluster analysis of large data sets in high-dimensional spaces

  1996cited by this paper
• A mixture likelihood approach for generalized linear models

  1995cited by this paper
• Space-alternating generalized expectation-maximization algorithm

  1994cited by this paper
• The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence

  1994cited by this paper
• A new view of the EM algorithm that justifies incremental and other variants

  1993cited by this paper
• Maximum likelihood estimation via the ECM algorithm: A general framework

  1993cited by this paper
• Model-based Gaussian and non-Gaussian clustering

  1993cited by this paper
• Classification and Clustering in Spatial and Image Data

  1992cited by this paper
• Statistical theory in clustering

  1985cited by this paper
• Estimating the Dimension of a Model

  1978cited by this paper
• A family of variable metric updates

  1977cited by this paper
• A new look at the statistical model identification

  1974cited by this paper
• Conditioning of Quasi-Newton Methods for Function Minimization

  1970cited by this paper
• The Convergence of a Class of Double-rank Minimization Algorithms 2. The New Algorithm

  1970cited by this paper
• A New Approach to Variable Metric Algorithms

  1970cited by this paper
• The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations

  1970cited by this paper
• A family of variable-metric methods derived by variational means

  1970cited by this paper
• A Simplex Method for Function Minimization

  1965cited by this paper
• LIII. On lines and planes of closest fit to systems of points in space

  1901cited by this paper

• Robust Model‐Based Semi‐Supervised Clustering of Incomplete Records

  2025cites this paper
• Model-based segmentation for improved activation detection in single-subject functional Magnetic Resonance Imaging studies

  2022cites this paper
• Prediction of Drought Severity Using Model-Based Clustering

  2021cites this paper
• A practical model‐based segmentation approach for improved activation detection in single‐subject functional magnetic resonance imaging studies

  2021influential citation
• A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies

  2021cites this paper
• Prediction for Various Drought Classes Using Spatiotemporal Categorical Sequences

  2021cites this paper
• Estimating basis functions in massive fields under the spatial random effects model

  2020cites this paper
• Estimating basis functions in massive fields under the spatial mixed effects model

  2020cites this paper
• Research on post-match score mechanism of players based on artificial intelligence and clustering regression model

  2020cites this paper
• RETRACTED: Analysis of regression prediction model of competitive sports based on SVM and artificial intelligence

  2020cites this paper
• Competition prediction and fitness behavior based on GA-SVM algorithm and PCA model

  2019cites this paper
• Gaussian-mixture-model-based cluster analysis finds five kinds of gamma-ray bursts in the BATSE catalogue

  2017cites this paper
• Adaptive usage of K-means in evolutionary optimized data clustering

  2017cites this paper
• Studying Complexity of Model-based Clustering

  2016cites this paper
• ClickClust: An R Package for Model-Based Clustering of Categorical Sequences

  2016cites this paper
• Merging Mixture Components for Clustering Through Pairwise Overlap

  2016cites this paper
• Finite Mixture Modeling of Gaussian Regression Time Series with Application to Dendrochronology

  2016cites this paper
• Adaptive Multisubpopulation Competition and Multiniche Crowding-Based Memetic Algorithm for Automatic Data Clustering

  2016cites this paper
• Spectral synchronicity in brain signals

  2015cites this paper
• Fuzzy Clustering of Series Using Quantile Autocovariances

  2015cites this paper
• Recent Developments in Model-Based Clustering with Applications

  2015cites this paper
• Semi-supervised model-based clustering with positive and negative constraints

  2015cites this paper
• A Parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data

  2013influential citation
• Alternative approaches to maximum likelihood estimation of the spatial random effects model

  2013influential citation
• Challenges in model‐based clustering

  2013cites this paper
• Efficient estimation in model‐based clustering of Gaussian regression time series

  2012influential citation