Sarkar, S., Zhu, X., Melnykov, V. and Ingrassia, S. (2019) On Parsimonious Models for Modeling Matrix Data, accepted by Computational Statistics and Data Analysis.

Melnykov, V. and Michael, S. (2019) Clustering Large Datasets by Merging K-Means Solutions, accepted by Journal of Classification.

Melnykov, V. and Zhu, X. (2019) An Extension of the K-Means Algorithm to Clustering Skewed Data, Computational Statistics, 34:1, 373-394.

Melnykov, V. and Zhu, X. (2019) Studying Crime Trends in the USA over the Years 2000-2012, Advances in Data Analysis and Classification, 13:1, 325-341.

Melnykov, V. and Zhu, X. (2018) On Model-Based Clustering of Skewed Matrix Data, Journal of Multivariate Analysis, 167, 181-194.

Zhu, X. and Melnykov, V. (2018) Manly Transformation in Finite Mixture Modeling, Computational Statistics and Data Analysis, 121, 190-208.

Zhu, X. and Melnykov, V. (2017) ManlyMix: An R Package for Manly Mixture Modeling, The R Journal, 9:2, 176-197.

Melnykov, Y., Melnykov, V. and Zhu, X. (2017) Studying Contributions of Variables to Classification, Statistics and Probability Letters, 129, 318-325.

Melnykov, V. (2016) ClickClust: An R Package for Model-Based Clustering of Categorical Sequences, Journal of Statistical Software, 74:9, 1-34.

Melnykov, V. (2016) Model-Based Biclustering of Clickstream Data, Computational Statistics and Data Analysis, 93, 31-45.

Melnykov, V. (2016) Merging Mixture Components for Clustering through Pairwise Overlap, Journal of Computational and Graphical Statistics, 25, 66-90.

Melnykov, V., Melnykov, I. and Michael, S. (2016) Semi-Supervised Model-Based Clustering with Positive and Negative Constraints, Advances in Data Analysis and Classification, 10:3, 327-349.

Michael, S. and Melnykov, V. (2016) Finite Mixture Modeling of Gaussian Regression Time Series with Application to Dendrochronology, Journal of Classification, 33:3, 412-441.

Michael, S. and Melnykov, V. (2016) An Effective Strategy for Initializing the EM algorithm in Finite Mixture Models, Advances in Data Analysis and Classification, 10:4, 563-583.

Michael, S. and Melnykov, V. (2016) Studying Complexity of Model-Based Clustering, Communications in Statistics – Simulation and Computation, 45:6, 2051-2069.

Zhu, X. and Melnykov, V. (2015) Probabilistic Assessment of Model-Based Clustering, Advances in Data Analysis and Classification, 9:4, 395-422.

Melnykov, V., Michael, S. and Melnykov, I. (2015) Recent Developments in Model-Based Clustering with Applications, Partitional Clustering Algorithms, ed. M. E. Celebi, Springer, 1-39.

Melnykov, I. and Melnykov, V. (2014) On K-Means Algorithm with the Use of Mahalanobis Distances, Statistics and Probability Letters, 84, 88-95.

Melnykov, V. (2013) On the Distribution of Posterior Probabilities in Finite Mixture Models with Application in Clustering, Journal of Multivariate Analysis, 122, 175-189.

Melnykov, V. (2013) Finite Mixture Modeling in Mass Spectrometry Analysis, Journal of the Royal Statistical Society: Series C, 62:4, 573-592.

Melnykov, V. (2013) Challenges in Model-Based Clustering, WIREs: Computational Statistics, 5:2, 135-148.

Melnykov, V. and Shen, G. (2013) Clustering through Empirical Likelihood Ratio, Computational Statistics and Data Analysis, 62, 1-10.

Melnykov, V., Chen, W.-C. and Maitra, R. (2012) MixSim: R Package for Simulating Datasets with Pre-Specified Clustering Complexity, Journal of Statistical Software, 51:12, 1-25.

Maitra, R., Melnykov, V. and Lahiri, S. (2012) Bootstrapping for Significance of Compact Clusters, Journal of the American Statistical Association, 107:497, 378-392.

Melnykov, V. and Melnykov, I. (2012) Initializing the EM Algorithm in Gaussian Mixture Models with an Unknown Number of Components, Computational Statistics and Data Analysis, 56:6, 1381-1395.

Melnykov, V. (2012) Efficient Estimation in Model-Based Clustering of Gaussian Regression Time Series, Statistical Analysis and Data Mining, 5:2, 95-99.

Melnykov, V., Maitra, R. and Nettleton, D. (2011) Accounting for Spot Matching Uncertainty in the Analysis of Proteomics Data from Two-Dimensional Gel Electrophoresis, Sankhya: Series B, 73:1, 123-143.

Melnykov, V. and Maitra, R. (2011) CARP: Software for Fishing Out Good Clustering Algorithms, Journal of Machine Learning Research, 12, 69-73.

Maitra, R. and Melnykov, V. (2010) Simulating Data to Study Performance of Finite Mixture Modeling and Clustering Algorithms, Journal of Computational and Graphical Statistics, 2:19, 354-376.

Melnykov, V. and Maitra, R. (2010) Finite Mixture Models and Model-Based Clustering, Statistics Surveys, 4, 80-116.