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Publication in the field of technical sciences
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Table of contents (6 chapters)
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Front Matter
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Back Matter
About this book
Paola Gloria Ferrario develops and investigates several methods of nonparametric local variance estimation. The first two methods use regression estimations (plug-in), achieving least squares estimates as well as local averaging estimates (partitioning or kernel type). Furthermore, the author uses a partitioning method for the estimation of the local variance based on first and second nearest neighbors (instead of regression estimation). Approaching specific problems of application fields, all the results are extended and generalised to the case where only censored observations are available. Further, simulations have been executed comparing the performance of two different estimators (R-Code available!). As a possible application of the given theory the author proposes a survival analysis of patients who are treated for a specific illness.
Authors and Affiliations
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Stuttgart, Germany
Paola Gloria Ferrario
About the author
Paola Gloria Ferrario received her doctorate degree (doctor rerum naturalium) from the University of Stuttgart, Germany, in 2012, after having studied Mathematical Engineering at the Polytechnic of Milano, Italy. She taught mathematics to students of economics at University of Hohenheim and now works as a researcher at the University of Lübeck, Germany.
Bibliographic Information
Book Title: Local Variance Estimation for Uncensored and Censored Observations
Authors: Paola Gloria Ferrario
DOI: https://doi.org/10.1007/978-3-658-02314-0
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2013
Softcover ISBN: 978-3-658-02313-3Published: 11 June 2013
eBook ISBN: 978-3-658-02314-0Published: 30 May 2013
Edition Number: 1
Number of Pages: XVII, 130
Number of Illustrations: 3 b/w illustrations
Topics: Mathematics, general