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A Tutorial on MM Algorithms

Citations

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Cited by:

  1. Vu, Duy & Aitkin, Murray, 2015. "Variational algorithms for biclustering models," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 12-24.
  2. Matthew Pietrosanu & Jueyu Gao & Linglong Kong & Bei Jiang & Di Niu, 2021. "Advanced algorithms for penalized quantile and composite quantile regression," Computational Statistics, Springer, vol. 36(1), pages 333-346, March.
  3. Norbert Remenyi & Xiaodong Luo, 2021. "Demand estimation from sales transaction data: practical extensions," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 276-300, June.
  4. de Leeuw, Jan & Lange, Kenneth, 2009. "Sharp quadratic majorization in one dimension," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2471-2484, May.
  5. Rodrigo Carvajal & Rafael Orellana & Dimitrios Katselis & Pedro Escárate & Juan Carlos Agüero, 2018. "A data augmentation approach for a class of statistical inference problems," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-24, December.
  6. Chen, Shu-Chuan (Grace) & Lindsay, Bruce, 2014. "Improving mixture tree construction using better EM algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 17-25.
  7. Rasmus Lentz & Suphanit Piyapromdee & Jean-Marc Robin, 2022. "The Anatomy of Sorting - Evidence from Danish Data," SciencePo Working papers Main hal-03869383, HAL.
  8. Wu, Tong Tong & Lange, Kenneth, 2015. "Matrix completion discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 92(C), pages 115-125.
  9. Lv, Xiao-Guang & Jiang, Le & Liu, Jun, 2016. "Deblurring Poisson noisy images by total variation with overlapping group sparsity," Applied Mathematics and Computation, Elsevier, vol. 289(C), pages 132-148.
  10. Rasmus Lentz & Suphanit Piyapromdee & Jean-Marc Robin, 2018. "On Worker and Firm Heterogeneity in Wages and Employment Mobility: Evidence from Danish Register Data," PIER Discussion Papers 91, Puey Ungphakorn Institute for Economic Research.
  11. Florian Schwendinger & Bettina Grün & Kurt Hornik, 2021. "A comparison of optimization solvers for log binomial regression including conic programming," Computational Statistics, Springer, vol. 36(3), pages 1721-1754, September.
  12. Sharon M. McNicholas & Paul D. McNicholas & Daniel A. Ashlock, 2021. "An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 264-279, July.
  13. Gunter Maris & Han Maas, 2012. "Speed-Accuracy Response Models: Scoring Rules based on Response Time and Accuracy," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 615-633, October.
  14. Yoshihiro Kanno, 2018. "Robust truss topology optimization via semidefinite programming with complementarity constraints: a difference-of-convex programming approach," Computational Optimization and Applications, Springer, vol. 71(2), pages 403-433, November.
  15. V. Maume-Deschamps & D. Rullière & A. Usseglio-Carleve, 2018. "Spatial Expectile Predictions for Elliptical Random Fields," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 643-671, June.
  16. Deng, Lifeng & Ding, Jieli & Liu, Yanyan & Wei, Chengdong, 2018. "Regression analysis for the proportional hazards model with parameter constraints under case-cohort design," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 194-206.
  17. Emilie Chouzenoux & Jean-Christophe Pesquet & Audrey Repetti, 2014. "Variable Metric Forward–Backward Algorithm for Minimizing the Sum of a Differentiable Function and a Convex Function," Journal of Optimization Theory and Applications, Springer, vol. 162(1), pages 107-132, July.
  18. Wu, Runxiong & Chen, Xin, 2021. "MM algorithms for distance covariance based sufficient dimension reduction and sufficient variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
  19. Tian, Guo-Liang & Tang, Man-Lai & Liu, Chunling, 2012. "Accelerating the quadratic lower-bound algorithm via optimizing the shrinkage parameter," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 255-265.
  20. Nguyen Thai An & Daniel Giles & Nguyen Mau Nam & R. Blake Rector, 2016. "The Log-Exponential Smoothing Technique and Nesterov’s Accelerated Gradient Method for Generalized Sylvester Problems," Journal of Optimization Theory and Applications, Springer, vol. 168(2), pages 559-583, February.
  21. Groenen, P.J.F. & Kaymak, U. & van Rosmalen, J.M., 2006. "Fuzzy clustering with Minkowski distance," Econometric Institute Research Papers EI 2006-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  22. Yen, Tso-Jung & Yen, Yu-Min, 2016. "Structured variable selection via prior-induced hierarchical penalty functions," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 87-103.
  23. Spyridon Samothrakis & Maria Fasli & Diego Perez & Simon Lucas, 2017. "Default policies for global optimisation of noisy functions with severe noise," Journal of Global Optimization, Springer, vol. 67(4), pages 893-907, April.
  24. Hirose, Kei & Fujisawa, Hironori & Sese, Jun, 2017. "Robust sparse Gaussian graphical modeling," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 172-190.
  25. Durante, Daniele & Canale, Antonio & Rigon, Tommaso, 2019. "A nested expectation–maximization algorithm for latent class models with covariates," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 97-103.
  26. Groenen, P.J.F. & Nalbantov, G.I. & Bioch, J.C., 2007. "SVM-Maj: a majorization approach to linear support vector machines with different hinge errors," Econometric Institute Research Papers EI 2007-49, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  27. Ouindllassida Jean-Etienne Ou´edraogo & Edoh Katchekpele & Simplice Dossou-Gb´et´e, 2021. "Marginalized Maximum Likelihood for Parameters Estimation of the Three Parameter Weibull Distribution," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(4), pages 1-62, July.
  28. Zhou, Hua & Zhang, Yiwen, 2012. "EM vs MM: A case study," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3909-3920.
  29. Songfeng Zheng, 2021. "KLERC: kernel Lagrangian expectile regression calculator," Computational Statistics, Springer, vol. 36(1), pages 283-311, March.
  30. Asger Hobolth & Qianyun Guo & Astrid Kousholt & Jens Ledet Jensen, 2020. "A Unifying Framework and Comparison of Algorithms for Non‐negative Matrix Factorisation," International Statistical Review, International Statistical Institute, vol. 88(1), pages 29-53, April.
  31. Sanjeena Subedi & Drew Neish & Stephen Bak & Zeny Feng, 2020. "Cluster analysis of microbiome data by using mixtures of Dirichlet–multinomial regression models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1163-1187, November.
  32. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
  33. Nguyen, Hien D. & McLachlan, Geoffrey J., 2016. "Laplace mixture of linear experts," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 177-191.
  34. Gruenhage, Gina & Opper, Manfred & Barthelme, Simon, 2016. "Visualizing the effects of a changing distance on data using continuous embeddings," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 51-65.
  35. Lian, Heng & Meng, Jie & Fan, Zengyan, 2015. "Simultaneous estimation of linear conditional quantiles with penalized splines," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 1-21.
  36. Landgraf, Andrew J. & Lee, Yoonkyung, 2020. "Dimensionality reduction for binary data through the projection of natural parameters," Journal of Multivariate Analysis, Elsevier, vol. 180(C).
  37. Gary K Chen & Eric C Chi & John Michael O Ranola & Kenneth Lange, 2015. "Convex Clustering: An Attractive Alternative to Hierarchical Clustering," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-31, May.
  38. Stéphane Chrétien & Alfred Hero & Hervé Perdry, 2012. "Space alternating penalized Kullback proximal point algorithms for maximizing likelihood with nondifferentiable penalty," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(4), pages 791-809, August.
  39. Sakyajit Bhattacharya & Paul McNicholas, 2014. "A LASSO-penalized BIC for mixture model selection," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(1), pages 45-61, March.
  40. Hien Nguyen & Geoffrey McLachlan, 2015. "Maximum likelihood estimation of Gaussian mixture models without matrix operations," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(4), pages 371-394, December.
  41. Nguyen Thai An & Nguyen Mau Nam & Xiaolong Qin, 2020. "Solving k-center problems involving sets based on optimization techniques," Journal of Global Optimization, Springer, vol. 76(1), pages 189-209, January.
  42. Utkarsh J. Dang & Michael P.B. Gallaugher & Ryan P. Browne & Paul D. McNicholas, 2023. "Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions," Journal of Classification, Springer;The Classification Society, vol. 40(1), pages 145-167, April.
  43. Green, Beth L. & Ayoub, Catherine & Bartlett, Jessica Dym & Von Ende, Adam & Furrer, Carrie & Chazan-Cohen, Rachel & Vallotton, Claire & Klevens, Joanne, 2014. "The effect of Early Head Start on child welfare system involvement: A first look at longitudinal child maltreatment outcomes," Children and Youth Services Review, Elsevier, vol. 42(C), pages 127-135.
  44. Yuhong Wei & Paul McNicholas, 2015. "Mixture model averaging for clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(2), pages 197-217, June.
  45. Ding, Jieli & Tian, Guo-Liang & Yuen, Kam Chuen, 2015. "A new MM algorithm for constrained estimation in the proportional hazards model," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 135-151.
  46. Xiaotian Zhu & David R. Hunter, 2019. "Clustering via finite nonparametric ICA mixture models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 65-87, March.
  47. Hosik Choi & Eunjung Song & Seung-sik Hwang & Woojoo Lee, 2018. "A modified generalized lasso algorithm to detect local spatial clusters for count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(4), pages 537-563, October.
  48. Xifen Huang & Jinfeng Xu & Yunpeng Zhou, 2022. "Profile and Non-Profile MM Modeling of Cluster Failure Time and Analysis of ADNI Data," Mathematics, MDPI, vol. 10(4), pages 1-21, February.
  49. Inoue, Masaaki & Pham, Thong & Shimodaira, Hidetoshi, 2020. "Joint estimation of non-parametric transitivity and preferential attachment functions in scientific co-authorship networks," Journal of Informetrics, Elsevier, vol. 14(3).
  50. Groenen, P.J.F. & Bioch, J.C. & Nalbantov, G.I., 2006. "Nonlinear support vector machines through iterative majorization and I-splines," Econometric Institute Research Papers EI 2006-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  51. Babkin, Sergii & Stewart, Jonathan R. & Long, Xiaochen & Schweinberger, Michael, 2020. "Large-scale estimation of random graph models with local dependence," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  52. van den Burg, G.J.J. & Groenen, P.J.F., 2014. "GenSVM: A Generalized Multiclass Support Vector Machine," Econometric Institute Research Papers EI 2014-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  53. Jason Hou-Liu & Ryan P. Browne, 2022. "Chimeral Clustering," Journal of Classification, Springer;The Classification Society, vol. 39(1), pages 171-190, March.
  54. Vrbik, Irene & McNicholas, Paul D., 2014. "Parsimonious skew mixture models for model-based clustering and classification," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 196-210.
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