Clustering via finite nonparametric ICA mixture models
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DOI: 10.1007/s11634-018-0338-x
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- Hunter D.R. & Lange K., 2004. "A Tutorial on MM Algorithms," The American Statistician, American Statistical Association, vol. 58, pages 30-37, February.
- De Veaux, Richard D., 1989. "Mixtures of linear regressions," Computational Statistics & Data Analysis, Elsevier, vol. 8(3), pages 227-245, November.
- Eddelbuettel, Dirk & Sanderson, Conrad, 2014. "RcppArmadillo: Accelerating R with high-performance C++ linear algebra," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1054-1063.
- Mian Huang & Runze Li & Shaoli Wang, 2013. "Nonparametric Mixture of Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 929-941, September.
- Xiaotian Zhu & David R. Hunter, 2016. "Theoretical grounding for estimation in conditional independence multivariate finite mixture models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(4), pages 683-701, October.
- M. Levine & D. R. Hunter & D. Chauveau, 2011. "Maximum smoothed likelihood for multivariate mixtures," Biometrika, Biometrika Trust, vol. 98(2), pages 403-416.
- repec:hal:spmain:info:hdl:2441/etefo8s8r89oamhnhiclqr530 is not listed on IDEAS
- Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin, 2016.
"Non-parametric estimation of finite mixtures from repeated measurements,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 211-229, January.
- Koen Jochmans & Stéphane Bonhomme & Jean-Marc Robin, 2015. "Nonparametric estimation of finite mixtures from repeated measurements," SciencePo Working papers Main hal-03568247, HAL.
- Koen Jochmans & Stéphane Bonhomme & Jean-Marc Robin, 2015. "Nonparametric estimation of finite mixtures from repeated measurements," Post-Print hal-03568247, HAL.
- Alessandra Guglielmi & Francesca Ieva & Anna M. Paganoni & Fabrizio Ruggeri & Jacopo Soriano, 2014. "Semiparametric Bayesian models for clustering and classification in the presence of unbalanced in-hospital survival," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 25-46, January.
- Peña, Daniel & Prieto, Francisco J. & Viladomat, Júlia, 2010. "Eigenvectors of a kurtosis matrix as interesting directions to reveal cluster structure," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 1995-2007, October.
- Patrick Bajari & Jinyong Hahn & Han Hong & Geert Ridder, 2011. "A Note On Semiparametric Estimation Of Finite Mixtures Of Discrete Choice Models With Application To Game Theoretic Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(3), pages 807-824, August.
- Cristina Butucea & Pierre Vandekerkhove, 2014. "Semiparametric Mixtures of Symmetric Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 227-239, March.
- David Hunter & Derek Young, 2012. "Semiparametric mixtures of regressions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 19-38.
- Eddelbuettel, Dirk & Francois, Romain, 2011. "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i08).
- Pierre Vandekerkhove, 2013. "Estimation of a semiparametric mixture of regressions model," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(1), pages 181-208, March.
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- Shen, Yunyi & Olson, Erik R. & Van Deelen, Timothy R., 2021. "Spatially explicit modeling of community occupancy using Markov Random Field models with imperfect observation: Mesocarnivores in Apostle Islands National Lakeshore," Ecological Modelling, Elsevier, vol. 459(C).
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Keywords
Independent component analysis; Kernel density estimation; Nonparametric estimation; Penalized smoothed likelihood; Unsupervised learning;All these keywords.
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