Springer Proceedings in Mathematics & Statistics

Analytical Methods in Statistics

AMISTAT, Liberec, Czech Republic, September 2019

Editors: Maciak, Matúš, Pešta, Michal, Schindler, Martin (Eds.)

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  • Highlights modern analytical methods in statistics and their extensions
  • Focuses on estimation, asymptotics, robustness, and stochastics models
  • Gathers contributions by experts in the field
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書籍の購入

イーブック ¥16,015
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-030-48814-7
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ハードカバー ¥20,019
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-030-48813-0
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Immediate ebook access, if available*, with your print order
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この書籍について

This book collects peer-reviewed contributions on modern statistical methods and topics, stemming from the third workshop on Analytical Methods in Statistics, AMISTAT 2019, held in Liberec, Czech Republic, on September 16-19, 2019. Real-life problems demand statistical solutions, which in turn require new and profound mathematical methods. As such, the book is not only a collection of solved problems but also a source of new methods and their practical extensions. The authoritative contributions focus on analytical methods in statistics, asymptotics, estimation and Fisher information, robustness, stochastic models and inequalities, and other related fields; further, they address e.g. average autoregression quantiles, neural networks, weighted empirical minimum distance estimators, implied volatility surface estimation, the Grenander estimator, non-Gaussian component analysis, meta learning, and high-dimensional errors-in-variables models.


著者について

Matúš Maciak is an Assistant Professor at the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. His research interests include innovative statistical approaches concerning nonparametric and semiparametric regression models, sparse fitting via convex optimization (atomic pursuit / LASSO), estimation under various shape constraints, robustness and quantiles, and changepoint detection and estimation within various data structures. He also has practical experience in applied statistics, especially in empirical econometrics and finance, insurance, ecology, and the medical sciences.

Michal Pešta is an Associate Professor at the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. His research interests include asymptotic methods for changepoint, weak dependence, copulae, resampling methods, panel data, nonparametric regression, and errors-in-variables modeling. He is also interested in developing complex statistical methodology frameworks for various real-life settings, including empirical econometrics, finance, and non-life insurance.

Martin Schindler is an Assistant Professor of Applied Mathematics at the Technical University of Liberec, Czech Republic. His research interests include robust and nonparametric statistics, statistical computing and simulations. He has also worked on various inference procedures based on regression rank scores used in both linear and nonlinear models. During his postdoctoral studies at the University of Tampere he worked on nonparametric procedures for microarray data.


Table of contents (8 chapters)

Table of contents (8 chapters)

書籍の購入

イーブック ¥16,015
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-030-48814-7
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: PDF, EPUB
  • どの電子書籍リーダーからでもすぐにお読みいただけます。
  • ご購入後、すぐにダウンロードしていただけます。
ハードカバー ¥20,019
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-030-48813-0
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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書誌情報

Bibliographic Information
Book Title
Analytical Methods in Statistics
Book Subtitle
AMISTAT, Liberec, Czech Republic, September 2019
Editors
  • Matúš Maciak
  • Michal Pešta
  • Martin Schindler
Series Title
Springer Proceedings in Mathematics & Statistics
Series Volume
329
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
イーブック ISBN
978-3-030-48814-7
DOI
10.1007/978-3-030-48814-7
ハードカバー ISBN
978-3-030-48813-0
Series ISSN
2194-1009
Edition Number
1
Number of Pages
X, 156
Number of Illustrations
7 b/w illustrations, 8 illustrations in colour
Topics

*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works and instructor copies are not included.