This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data.
Key features:
Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Georgy L. Shevlyakov, Department of Applied Mathematics, St. Petersburg State Polytechnic University, Russia
Hannu Oja, School of Health Sciences, University of Tampere, Finland
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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