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Topics in Nonparametric Estimation - Soviet Mathematics Book

Applied Mathematics

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Description

Explore advanced mathematical research with Topics in Nonparametric Estimation, part of the Advances in Soviet Mathematics series. This volume brings together essential papers from the Seminar on Mathematical Statistics held at the Institute for Problems of Information Transmission of the Academy of Sciences. Since its founding in the mid-1960s, this seminar has served as a primary hub for researchers in Moscow dedicated to mathematical statistics. This collection provides deep insights into complex statistical methods and theories. It covers a wide range of specialized subjects including density, regression, and image estimation, as well as adaptive estimation and stochastic approximation. Readers will also find detailed discussions on median estimation, sequential experimental design, and large deviations for empirical measures. This book serves as a valuable resource for academics and professionals looking to engage with high-level mathematical scholarship from a historically significant research seminar.

Key Features

Contains research papers from the prestigious Seminar on Mathematical Statistics at the Institute for Problems of Information Transmission.

Covers essential statistical topics such as density, regression, and image estimation for advanced study.

Includes detailed content on adaptive estimation and stochastic approximation techniques.

Provides specialized mathematical analysis on median estimation and sequential experimental design.

Explores complex theories regarding large deviations for empirical measures.

Part of the respected Advances in Soviet Mathematics series published by the American Mathematical Society.

Product Specifications

Format: hardcover
ASIN: 0821841114
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Applied Mathematics
Domain: Amazon UK
Release Date: 28 January 1993
Listed Since: 17 October 2006

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Topics in Nonparametric Estimation - Soviet Mathematics Book

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