Analytical Methods in Statistics AMISTAT, Prague, November 2015 /
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 approxi...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , , , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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Σειρά: | Springer Proceedings in Mathematics & Statistics,
193 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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 Jurečková)
- 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 Zdeněk 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).