References in zbMATH (referenced in 58 articles , 1 standard article )

1. Dychko, H. M.; Maĭboroda, R. E.: A generalized Nadaraya-Watson estimator for observations obtained from a mixture (2020)
2. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
3. Murphy, Keefe; Murphy, Thomas Brendan: Gaussian parsimonious clustering models with covariates and a noise component (2020)
4. Zheng, Chaowen; Wu, Yichao: Nonparametric estimation of multivariate mixtures (2020)
5. Akakpo, Rexford M.; Xia, Michelle; Polansky, Alan M.: Frequentist inference in insurance ratemaking models adjusting for misrepresentation (2019)
6. Blair R. Drummond, Christian J.G. Tessier, Mathieu F. Dextraze, Corrie J.B. daCosta: scbursts: An R package for analysis and sorting of single-channel bursts (2019) not zbMATH
7. Comas-Cufí, Marc; Martín-Fernández, Josep A.; Mateu-Figueras, Glòria: Merging the components of a finite mixture using posterior probabilities (2019)
8. Geissen, Eva-Maria; Hasenauer, Jan; Radde, Nicole E.: Inference of finite mixture models and the effect of binning (2019)
9. Gualandi, Stefano; Toscani, Giuseppe: Human behavior and lognormal distribution. A kinetic description (2019)
10. Lim, Johan; Yu, Donghyeon; Kuo, Hsun-Chih; Choi, Hyungwon; Walmsley, Scott: Truncated rank correlation (TRC) as a robust measure of test-retest reliability in mass spectrometry data (2019)
11. Liu, Yiyi; Warren, Joshua L.; Zhao, Hongyu: A hierarchical Bayesian model for single-cell clustering using RNA-sequencing data (2019)
12. Maĭboroda, R. E.; Navara, G. V.; Sugakova, O. V.: Orthogonal regression method for observations from a mixture (2019)
13. Michael Hahsler; Matthew Piekenbrock; Derek Doran: dbscan: Fast Density-Based Clustering with R (2019) not zbMATH
14. Nguyen, Hien; Yee, Yohan; McLachlan, Geoffrey; Lerch, Jason: False discovery rate control for grouped or discretely supported (p)-values with application to a neuroimaging study (2019)
15. Young, Derek S.; Chen, Xi; Hewage, Dilrukshi C.; Nilo-Poyanco, Ricardo: Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering (2019)
16. Zagaris, Antonios: Data-informed modeling in the health sciences (2019)
17. Alexander Foss; Marianthi Markatou: kamila: Clustering Mixed-Type Data in R and Hadoop (2018) not zbMATH
18. Angelo Mazza; Antonio Punzo; Salvatore Ingrassia: flexCWM: A Flexible Framework for Cluster-Weighted Models (2018) not zbMATH
19. Fop, Michael; Murphy, Thomas Brendan: Variable selection methods for model-based clustering (2018)
20. Ghosh, I.; Hamedani, G. G.; Bansal, N.; Maadooliat, M.: On the mixtures of Weibull and Pareto (IV) distribution: an alternative to Pareto distribution (2018)