Springer Proceedings in Mathematics & Statistics

Analytical Methods in Statistics

AMISTAT, Prague, November 2015

Editors: Antoch, J., Jurečková, J., Maciak, M., Pešta, M. (Eds.)

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  • Features new results in estimation theory, hypothesis testing and regression, including quantile regression and divergence minimization
  • Elaborates on analytical properties of probability distributions and resampling techniques
  • Presents robust and nonparametric inference under shape constraints and inference for weakly dependent data
  • Collates the latest contributions by experts in the field
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About this book

This volume collects authoritative contributions on analytical methods and mathematical statistics. The methods presented include resampling techniques; the minimization of divergence; estimation theory and regression, eventually under shape or other constraints or long memory; and iterative approximations when the optimal solution is difficult to achieve. It also investigates probability distributions with respect to their stability, heavy-tailness, Fisher information and other aspects, both asymptotically and non-asymptotically. The book not only presents the latest mathematical and statistical methods and their extensions, but also offers solutions to real-world problems including option pricing. The selected, peer-reviewed contributions were originally presented at the workshop on Analytical Methods in Statistics, AMISTAT 2015, held in Prague, Czech Republic, November 10-13, 2015.

About the authors

Jaromír Antoch is a full professor at the Charles University in Prague. His research interests include statistical computing, simulations, change point detection, robust and nonparametric statistics, industrial statistics and applications. He was chairman of the European Regional Section of the International Association for Statistical Computing (IASC) Board of Directors, president of IASC and council member of the International Statistical Institute.

Jana Jurečková is a full professor at the Charles University in Prague. She has published over 130 papers in leading journals and coauthored 5 monographs. She has worked on relationships and behavior of robust estimators and nonparametric procedures since the 1970s. She has worked as a visiting professor in Belgium, France, Italy, Switzerland and the USA. She is elected member of the International Statistical Institute, fellow of the Institute of Mathematical Statistics, member of the Bernoulli Society Council and of the ASA Noether’s Award Committee.

Matúš Maciak is an assistant professor at the Charles University in Prague. His research work focuses on nonparametric estimation methods, change point detection and robustness. Recently he elaborated contemporary ideas in sparse fitting via convex optimization – atomic pursuit and lasso. He also gained experience during his stays at the University of Alberta in Edmonton, Hasselt University and the University of Hamburg. 

Michal Pešta is an assistant professor at the Charles University in Prague. His research interests include asymptotic methods for weak dependence, resampling methods, panel data, nonparametric regression, and errors-in-variables modeling. In the recent years, he has been developing the statistical methodology for non-life insurance. Michal Pešta has utilized the skills gained during his PhD and postdoctoral stays (Hasselt University, University of Hamburg, HU Berlin, University of Alberta) to contribute to applied fields.

 

Table of contents (9 chapters)

Table of contents (9 chapters)
  • A Weighted Bootstrap Procedure for Divergence Minimization Problems

    Broniatowski, Michel

    Pages 1-22

  • Asymptotic Analysis of Iterated 1-Step Huber-Skip M-Estimators with Varying Cut-Offs

    Jiao, Xiyu (et al.)

    Pages 23-52

  • Regression Quantile and Averaged Regression Quantile Processes

    Jurečková, Jana

    Pages 53-62

  • Stability and Heavy-Tailness

    Klebanov, Lev B.

    Pages 63-72

  • Smooth Estimation of Error Distribution in Nonparametric Regression Under Long Memory

    Koul, Hira L. (et al.)

    Pages 73-104

Buy this book

eBook $99.00
price for USA in USD (gross)
  • ISBN 978-3-319-51313-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA in USD
  • ISBN 978-3-319-51312-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $129.00
price for USA in USD
  • ISBN 978-3-319-84617-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Analytical Methods in Statistics
Book Subtitle
AMISTAT, Prague, November 2015
Editors
  • Jaromír Antoch
  • Jana Jurečková
  • Matúš Maciak
  • Michal Pešta
Series Title
Springer Proceedings in Mathematics & Statistics
Series Volume
193
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-51313-3
DOI
10.1007/978-3-319-51313-3
Hardcover ISBN
978-3-319-51312-6
Softcover ISBN
978-3-319-84617-0
Series ISSN
2194-1009
Edition Number
1
Number of Pages
IX, 207
Number of Illustrations
8 b/w illustrations, 4 illustrations in colour
Topics