Comments on “The power of monitoring: how to make the most of a contaminated multivariate sample”
暂无分享,去创建一个
[1] Luis Angel García-Escudero,et al. Finding the Number of Normal Groups in Model-Based Clustering via Constrained Likelihoods , 2018 .
[2] Peter Filzmoser,et al. Robust fitting of mixtures using the trimmed likelihood estimator , 2007, Comput. Stat. Data Anal..
[3] Gunter Ritter,et al. Using combinatorial optimization in model-based trimmed clustering with cardinality constraints , 2010, Comput. Stat. Data Anal..
[4] Luis Angel García-Escudero,et al. Trimming Tools in Exploratory Data Analysis , 2003 .
[5] Carlos Matrán,et al. Robust estimation in the normal mixture model based on robust clustering , 2008 .
[6] Alfonso Gordaliza Ramos,et al. A general trimming approach to robust cluster analysis , 2007 .
[7] Luis Angel García-Escudero,et al. The importance of the scales in heterogeneous robust clustering , 2007, Comput. Stat. Data Anal..
[8] Luis Angel García-Escudero,et al. Exploring the number of groups in robust model-based clustering , 2011, Stat. Comput..
[9] Luis Angel García-Escudero,et al. A reweighting approach to robust clustering , 2017, Statistics and Computing.
[10] J. A. Cuesta-Albertos,et al. Trimmed $k$-means: an attempt to robustify quantizers , 1997 .
[11] Anthony C. Atkinson,et al. The power of monitoring: how to make the most of a contaminated multivariate sample , 2018, Stat. Methods Appl..