Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Описание: As a hospital physician it is impossible to escape the notion that the difficult medical problems one encounters are also being confronted by other` physicians throughout the world. One serious consequence of these characteristics of the medical literature is that patients are largely overtreated.
Автор: Fengler Matthias R. Название: Semiparametric Modeling of Implied Volatility ISBN: 3540262342 ISBN-13(EAN): 9783540262343 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The implied volatility surface is a key financial variable for the pricing and the risk management of plain vanilla and exotic options portfolios alike. Consequently, statistical models of the implied volatility surface are of immediate importance in practice: they may appear as estimates of the current surface or as fully specified dynamic models describing its propagation through space and time.This book fills a gap in the financial literature by bringing together both recent advances in the theory of implied volatility and refined semiparametric estimation strategies and dimension reduction methods for functional surfaces: the first part of the book is devoted to smile-consistent pricing appoaches. The theory of implied and local volatility is presented concisely, and vital smile-consistent modeling approaches such as implied trees, mixture diffusion, or stochastic implied volatility models are discussed in detail. The second part of the book familiarizes the reader with estimation techniques that are natural candidates to meet the challenges in implied volatility modeling, such as the rich functional structure of observed implied volatility surfaces and the necessity for dimension reduction: non- and semiparametric smoothing techniques.The book introduces Nadaraya-Watson, local polynomial and least squares kernel smoothing, and dimension reduction methods such as common principle components, functional principle components models and dynamic semiparametric factor models. Throughout, most methods are illustrated with empirical investigations, simulations and pictures.
Описание: This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.
Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis and related fields.
Specific topics covered include:
* non-parametric estimation of lifetimes of subjects exposed to radiation
* statistical analysis of simultaneous degradation-mortality data with covariates of the aged
* estimation of maintenance efficiency in semiparametric imperfect repair models
* cancer prognosis using survival forests
* short-term health problems related to air pollution: analysis using semiparametric generalized additive models
* parametric models in accelerated life testing and fuzzy data
* semiparametric models in the studies of aging and longevity
This book will be of use as a reference text for general statisticians, theoreticians, graduate students, reliability engineers, health researchers, and biostatisticians working in applied probability and statistics.
Автор: Hardle, Wolfgang Karl Muller, Marlene Sperlich, Stefan Werwatz, Axel Название: Nonparametric and semiparametric models ISBN: 3642620760 ISBN-13(EAN): 9783642620768 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers.
Описание: Kosorok`s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods.
Автор: David Ruppert Название: Semiparametric Regression ISBN: 0521785162 ISBN-13(EAN): 9780521785167 Издательство: Cambridge Academ Рейтинг: Цена: 8237.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.
Автор: Alex Gammerman Название: Causal Models and Intelligent Data Management ISBN: 3642636829 ISBN-13(EAN): 9783642636820 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. This book presents new intelligent data management methods and tools, including new results from the field of inference.
Автор: Johann Pfanzagl Название: Estimation in Semiparametric Models ISBN: 0387972382 ISBN-13(EAN): 9780387972381 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Assume one has to estimate the mean J x P( dx) (or the median of P, or any other functional t;;(P)) on the basis ofi.i.d. If P is known to be the member of a certain parametric family, say {Po: {) E e}, one can usually do better by estimating {) first, say by {)(n)(.~.), and using J XPo(n)(;r.) (dx) as an estimate for J xPo(dx).
Автор: Ruppert Название: Semiparametric Regression ISBN: 0521780500 ISBN-13(EAN): 9780521780506 Издательство: Cambridge Academ Рейтинг: Цена: 19800.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.
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