Analytical Methods in Statistics
AMISTAT, Prague, November 2015
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Beschreibung
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.
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.
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 Includes supplementary material: sn.pub/extras
Autor*in
Jaromír Antoch
Themen in »Analytical Methods in Statistics«
62E20, 62F05, 62F12, 62Jxx, 62G08, 60Gxx, 62Mxx, 62F40 statistical inference estimation and hypothesis testing regression stochastic processes bootstrap quantile regression heavy tails long-memory processes shape constrains asymptotic analysis minimization of divergence resampling Fisher information probability distribution