Improving the EM algorithm for mixtures. - Dimitris Karlis; Evdokia Xekalaki (Stat. Comput., 1999)

Unsupervised stratification of cross-validation for accuracy estimation. - N. A. Diamantidis; Dimitris Karlis; Emmanouel A. Giakoumakis (Artif. Intell., 2000)

Choosing initial values for the EM algorithm for finite mixtures. - Dimitris Karlis; Evdokia Xekalaki (Comput. Stat. Data Anal., 2003)

Multivariate Poisson regression with covariance structure. - Dimitris Karlis; Loukia Meligkotsidou (Stat. Comput., 2005)

Using Fuzzy Set Theory to Assess Country-of-Origin Effects on the Formation of Product Attitude. - Kris Brijs; Koen Vanhoof; Tom Brijs; Dimitris Karlis (MDAI, 2006)

Confidence intervals of the hazard rate function for discrete distributions using mixtures. - Dimitris Karlis; Valentin Patilea (Comput. Stat. Data Anal., 2007)

Copula model evaluation based on parametric bootstrap. - Aristidis K. Nikoloulopoulos; Dimitris Karlis (Comput. Stat. Data Anal., 2008)

Exact Bayesian modeling for bivariate Poisson data and extensions. - Dimitris Karlis; Panagiotis Tsiamyrtzis (Stat. Comput., 2008)

A note on the exponential Poisson distribution: A nested EM algorithm. - Dimitris Karlis (Comput. Stat. Data Anal., 2009)

Model-based clustering with non-elliptically contoured distributions. - Dimitris Karlis; Anais Santourian (Stat. Comput., 2009)

Modeling Multivariate Count Data Using Copulas. - Aristidis K. Nikoloulopoulos; Dimitris Karlis (Commun. Stat. Simul. Comput., 2010)

A finite mixture of bivariate Poisson regression models with an application to insurance ratemaking. - Lluís Bermúdez; Dimitris Karlis (Comput. Stat. Data Anal., 2012)

Some properties of multivariate INAR(1) processes. - Xanthi Pedeli; Dimitris Karlis (Comput. Stat. Data Anal., 2013)

On Estimation of the Bivariate Poisson INAR Process. - Xanthi Pedeli; Dimitris Karlis (Commun. Stat. Simul. Comput., 2013)

Clustering Dependencies Via Mixtures of Copulas. - Veni Arakelian; Dimitris Karlis (Commun. Stat. Simul. Comput., 2014)

Validation tests for the innovation distribution in INAR time series models. - Simos G. Meintanis; Dimitris Karlis (Comput. Stat., 2014)

Clustering with the multivariate normal inverse Gaussian distribution. - Adrian O'Hagan; Thomas Brendan Murphy; Isobel Claire Gormley; Paul D. McNicholas; Dimitris Karlis (Comput. Stat. Data Anal., 2016)

Model-based clustering using copulas with applications. - Ioannis Kosmidis; Dimitris Karlis (Stat. Comput., 2016)

A finite mixture of multiple discrete distributions for modelling heaped count data. - Lluís Bermúdez; Dimitris Karlis; Miguel Santolino (Comput. Stat. Data Anal., 2017)

Clustering discrete-valued time series. - Tyler Roick; Dimitris Karlis; Paul D. McNicholas (Adv. Data Anal. Classif., 2021)

Infinite Mixtures of Multivariate Normal-Inverse Gaussian Distributions for Clustering of Skewed Data. - Yuan Fang; Dimitris Karlis; Sanjeena Subedi (J. Classif., 2022)

Football tracking data: a copula-based hidden Markov model for classification of tactics in football. - Marius Ötting; Dimitris Karlis (Ann. Oper. Res., 2023)

Subdata selection for big data regression: an improved approach. - Vasilis Chasiotis; Dimitris Karlis (J. Data Sci. Stat. Vis., 2024)

A model-based approach to shot charts estimation in basketball. - Luca Scrucca; Dimitris Karlis (Comput. Stat., 2025)