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Nonparametric Estimation

This book offers a fresh introductory overview of nonparametric statistics, accessible already at a master’s level. Only basic knowledge in Probability and parametric estimation is necessary for understanding this very clear and detailed textbook.


It aims at clarifying the methods used in building curve estimators, and presenting the general tools used to assert the good performances of the proposed strategies. Two ways of reading are possible: on one hand, one can focus on practical ideas, alongside with elementary Matlab programs for their implementation; on the other, it presents rigorous results with theoretical proofs, ranging from the simplest ones to some more elaborated matters.


Thereby, starting naturally from elementary concepts in Probability and Statistics, the reader can progressively familiarize himself with all of the research topics in this domain, making this book very well suited for both master students — the book also provides exercises and corrected problems in order to reinforce the knowledge — and young researchers interested in the topic.

Détails

Fabienne Comte

Fabienne Comte is Professor at the University Paris Descartes (Paris V), France, where she has been teaching for many years a course on non-parametric estimation within the Master 2 program "Modelization and Statistics for Biology" and the Master's course "Mathematical Engineering for Life Sciences", of which she was in charge for ten years.

Alumna of École Normale Supérieure (Cachan), agrégée of Mathematics, she is equally involved in education and research. She was also a member of various scientific committees (National Committee of the CNRS, ANR, CNU, FSMP) and has recently become Head of Department of the MAP5, UMR8145, the laboratory of applied mathematics in which she is working.


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