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Antoch / Jurecková / Maciak

Analytical Methods in Statistics

AMISTAT, Prague, November 2015

Medium: Buch
ISBN: 978-3-319-51312-6
Verlag: Springer
Erscheinungstermin: 28.01.2017
Lieferfrist: bis zu 10 Tage

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.


Produkteigenschaften


  • Artikelnummer: 9783319513126
  • Medium: Buch
  • ISBN: 978-3-319-51312-6
  • Verlag: Springer
  • Erscheinungstermin: 28.01.2017
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2017
  • Serie: Springer Proceedings in Mathematics & Statistics
  • Produktform: Gebunden, HC runder Rücken kaschiert
  • Gewicht: 4557 g
  • Seiten: 207
  • Format (B x H x T): 160 x 241 x 18 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

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 Jurecková ) .-  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 ( Matúš Maciak ) .-  Shape Constrained Regression in Sobolev Spaces with Application to Option Pricing ( Michal Pešta and Zdenek Hlávka ) .- 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 ).