Alfonso Gordaliza Ramos-rekin lankidetzan egindako argitalpenak (17)

2018

  1. Comments on “The power of monitoring: how to make the most of a contaminated multivariate sample”

    Statistical Methods and Applications, Vol. 27, Núm. 4, pp. 605-608

2015

  1. Avoiding Spurious Local Maximizers in Mixture Modeling

    XXXV Congreso Nacional SEIO: IX Jornadas de Estadística Pública : Universidad Pública de Navarra, Pamplona, del 26 al 29 de mayo de 2015

  2. Avoiding spurious local maximizers in mixture modeling

    Statistics and Computing, Vol. 25, Núm. 3, pp. 619-633

  3. Robustness and outliers

    Handbook of Cluster Analysis (CRC Press), pp. 653-678

2013

  1. Grouping around different dimensional affine subspaces

    Studies in Classification, Data Analysis, and Knowledge Organization

2011

  1. Exploring the number of groups in robust model-based clustering

    Statistics and Computing, Vol. 21, Núm. 4, pp. 585-599

2010

  1. A review of robust clustering methods

    Advances in Data Analysis and Classification, Vol. 4, Núm. 2, pp. 89-109

2009

  1. A robust maximal F-ratio statistic to detect clusters structure

    Communications in Statistics - Theory and Methods, Vol. 38, Núm. 5, pp. 682-694

  2. Búsqueda robusta de curvas

    XXXI Congreso Nacional de Estadística e Investigación Operativa ; V Jornadas de Estadística Pública: Murcia, 10-13 de febrero de 2009 : Libro de Actas

2008

  1. A general trimming approach to robust cluster analysis

    Annals of Statistics, Vol. 36, Núm. 3, pp. 1324-1345

2007

  1. A general trimming approach to robust cluster analysis

    XXX Congreso Nacional de Estadística e Investigación Operativa y de las IV Jornadas de Estadística Pública: actas

2003

  1. Trimming tools in exploratory data analysis

    Journal of Computational and Graphical Statistics, Vol. 12, Núm. 2, pp. 434-449

1999

  1. A central limit theorem for multivariate generalized trimmed k-means

    Annals of Statistics, Vol. 27, Núm. 3, pp. 1061-1079

1998

  1. On the geometric behaviour of multidimensional location measures

    Journal of Statistical Planning and Inference, Vol. 67, Núm. 2, pp. 191-208

  2. Trimmed best k-nets: A robustified version of an L∞-based clustering method1

    Statistics and Probability Letters, Vol. 36, Núm. 4, pp. 401-413

1997

  1. Trimmed k-means: An attempt to robustify quantizers

    Annals of Statistics, Vol. 25, Núm. 2, pp. 553-576

1995

  1. Trimmed k-means and the Cauchy mean-value property

    NEW TRENDS IN PROBABILITY AND STATISTICS, VOL 3