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The goal of this text is to provide the reader with a single book where they can find a brief account of many, modern topics in nonparametric inference. The book is aimed at Master's level or Ph.D. level students in statistics, computer science,[...]
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The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. It covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics li[...]
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Gareth Michael James, - Auteur ; D. Witten, - Auteur ; Trevor J Hastie, - Auteur ; R. Tibshirani, - Auteur | London [GB] : Springer | Springer texts in statistics, ISSN 1431-875X | 2021"An Introduction to Statistical Learning" provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance t[...]
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Gareth Michael James, - Auteur ; D. Witten, - Auteur ; Trevor J Hastie, - Auteur | London [GB] : Springer | Springer texts in statistics, ISSN 1431-875X | 2013
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Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined simultaneously to get the most informative results. This requires the use of one or other of the many methods of multivariat[...]
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C. Robert ; G. Casella | London [GB] : Springer | Springer texts in statistics, ISSN 1431-875X | 2004Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of thes[...]
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R. Shumway ; D. Stoffer | London [GB] : Springer | Springer texts in statistics, ISSN 1431-875X | 2011This book presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory.
