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Statistical Inference in Finan cial and Insurance Mathematics with R, Brouste Alexandre


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Автор: Brouste Alexandre
Название:  Statistical Inference in Finan cial and Insurance Mathematics with R
Перевод названия: Александр Бруст: Статистические выводы в финансах и страховании
ISBN: 9781785480836
Издательство: Elsevier Science
Классификация:

ISBN-10: 1785480839
Обложка/Формат: Hardcover
Страницы: 150
Вес: 0.52 кг.
Дата издания: 22.11.2017
Язык: English
Размер: 236 x 158 x 18
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and identically distributed random variables are frequent and well understood, especially those consisting of probability measures of an exponential type. However, the aforementioned applications also offer non-classical experiments implying observation samples of independent but not identically distributed random variables or even dependent random variables.

Three examples of such experiments are treated in this book. First, the Generalized Linear Models are studied. They extend the standard regression model to non-Gaussian distributions. Statistical experiments with Markov chains are considered next. Finally, various statistical experiments generated by fractional Gaussian noise are also described.

In this book, asymptotic properties of several sequences of estimators are detailed. The notion of asymptotical efficiency is discussed for the different statistical experiments considered in order to give the proper sense of estimation risk. Eighty examples and computations with R software are given throughout the text.

  • Examines a range of statistical inference methods in the context of finance and insurance applications
  • Presents the LAN (local asymptotic normality) property of likelihoods
  • Combines the proofs of LAN property for different statistical experiments that appears in financial and insurance mathematics
  • Provides the proper description of such statistical experiments and invites readers to seek optimal estimators (performed in R) for such statistical experiments


Essential Statistical Inference

Автор: Boos
Название: Essential Statistical Inference
ISBN: 1461448174 ISBN-13(EAN): 9781461448174
Издательство: Springer
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Цена: 102480.00 T
Наличие на складе: Поставка под заказ.
Описание: A superb resource on statistical inference for researchers or students, this book has R code throughout, including in sample problems, and an appendix of derived notation and formulae. It covers core topics as well as modern aspects such as M-estimation.

Methods for estimation and inference in modern econometrics

Автор: Anatolyev, Stanislav Gospodinov, Nikolay
Название: Methods for estimation and inference in modern econometrics
ISBN: 1439838240 ISBN-13(EAN): 9781439838242
Издательство: Taylor&Francis
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Цена: 102080.00 T
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Описание:

Methods for Estimation and Inference in Modern Econometrics provides a comprehensive introduction to a wide range of emerging topics, such as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed in detail outside of highly technical research papers. The book also addresses several problems often arising in the analysis of economic data, including weak identification, model misspecification, and possible nonstationarity. The book's appendix provides a review of some basic concepts and results from linear algebra, probability theory, and statistics that are used throughout the book.





Topics covered include:







  • Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference


  • Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models


  • Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences






Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.


Causal Inference for Statistics, Social, and Biomedical Sciences

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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Цена: 54910.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Probability Theory and Statistical Inference

Название: Probability Theory and Statistical Inference
ISBN: 0521424089 ISBN-13(EAN): 9780521424080
Издательство: Cambridge Academ
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Цена: 48570.00 T
Наличие на складе: Поставка под заказ.
Описание: This major new textbook from a distinguished econometrician is intended for students taking introductory courses in probability theory and statistical inference. No prior knowledge other than a basic familiarity with descriptive statistics is assumed. The primary objective of this book is to establish the framework for the empirical modelling of observational (non-experimental) data. This framework known as 'Probabilistic Reduction' is formulated with a view to accommodating the peculiarities of observational (as opposed to experimental) data in a unifying and logically coherent way. Probability Theory and Statistical Inference differs from traditional textbooks in so far as it emphasizes concepts, ideas, notions and procedures which are appropriate for modelling observational data. Aimed at students at second-year undergraduate level and above studying econometrics and economics, this textbook will also be useful for students in other disciplines which make extensive use of observational data, including finance, biology, sociology and psychology and climatology.

A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935

Автор: Hald Anders
Название: A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935
ISBN: 0387464085 ISBN-13(EAN): 9780387464084
Издательство: Springer
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Цена: 111790.00 T
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Описание: This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.The book is divided into five main sections:* Binomial statistical inference;* Statistical inference by inverse probability;* The central limit theorem and linear minimum variance estimation by Laplace and Gauss;* Error theory, skew distributions, correlation, sampling distributions;* The Fisherian Revolution, 1912-1935.Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher.This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.


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