Analytical methods in statistics : AMISTAT, Prague, November 2015
著者
書誌事項
Analytical methods in statistics : AMISTAT, Prague, November 2015
（Springer proceedings in mathematics & statistics, v. 193）
Springer, c2017
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注記
Includes bibliographical references
"Workshop Analytical Methods in Statistics (AMISTAT) which was held in Prague during November 10-13, 2015" -- Pref.
Other editors: Jana Jurečková, Matúš Maciak, Michal Pešta
内容説明・目次
内容説明
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.
目次
Preface.- A Weighted Bootstrap Procedure for Divergence Minimization Problems (Michel Broniatowski).- Asymptotic Analysis of Iterated 1-step Huber-skip M-estimators with Varying Cut-offs (Xiyu Jiao and Bent Nielsen).-Regression Quantile and Averaged Regression Quantile Processes (Jana Jureckova).- Stability and Heavy-tailness (Lev B. Klebanov).- Smooth Estimation of Error Distribution in Nonparametric Regression under Long Memory (Hira L. Koul and Lihong Wang).- Testing Shape Constrains in Lasso Regularized Joinpoint Regression (Matus Maciak).- Shape Constrained Regression in Sobolev Spaces with Application to Option Pricing (Michal Pesta and Zdenek Hlavka).- On Existence of Explicit Asymptotically Normal Estimators in Non-Linear Regression Problems (Alexander Sakhanenko).- On the Behavior of the Risk of a LASSO-Type Estimator (Silvelyn Zwanzig and M. Rauf Ahmad).
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