Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Название: Probability Theory and Statistical Inference ISBN: 0521424089 ISBN-13(EAN): 9780521424080 Издательство: Cambridge Academ Рейтинг: 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.
Автор: Thorsten Dickhaus Название: Simultaneous Statistical Inference ISBN: 3642451810 ISBN-13(EAN): 9783642451812 Издательство: Springer Рейтинг: Цена: 148020.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This monograph offers an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate and related error measures, particularly addressing applications to such fields as genetics, proteomics and neuroscience.
Автор: Larson Название: Introduction to Probability Theory And Statistical Inference 3e ISBN: 0471059099 ISBN-13(EAN): 9780471059097 Издательство: Wiley Рейтинг: Цена: 275560.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discusses probability theory and to many methods used in problems of statistical inference. The Third Edition features material on descriptive statistics. Cramer-Rao bounds for variance of estimators, two-sample inference procedures, bivariate normal probability law, F-Distribution, and the analysis of variance and non-parametric procedures.
Автор: L. Bauwens Название: Bayesian Full Information Analysis of Simultaneous Equation Models Using Integration by Monte Carlo ISBN: 3540133844 ISBN-13(EAN): 9783540133841 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In their review of the "Bayesian analysis of simultaneous equation systems", Dr ze and Richard (1983) - hereafter DR - express the following viewpoint about the present state of development of the Bayesian full information analysis of such sys- tems i) the method allows "a flexible specification of the prior density, including well defined noninformative prior measures"; ii) it yields "exact finite sample posterior and predictive densities". However, they call for further developments so that these densities can be eval- uated through 'numerical methods, using an integrated software packa e. To that end, they recommend the use of a Monte Carlo technique, since van Dijk and Kloek (1980) have demonstrated that "the integrations can be done and how they are done". In this monograph, we explain how we contribute to achieve the developments suggested by Dr ze and Richard. A basic idea is to use known properties of the porterior density of the param- eters of the structural form to design the importance functions, i. e. approximations of the posterior density, that are needed for organizing the integrations.
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
Автор: T. Calinski; W. Klonecki Название: Linear Statistical Inference ISBN: 0387962557 ISBN-13(EAN): 9780387962559 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An International Statistical Conference on Linear Inference was held in Poznan, Poland, on June 4-8, 1984. If the conference was really a success, it was due to all its participants who in various ways were devoting their time and efforts to make the conference fruitful and enjoyable.
Автор: D.A. Sprott Название: Statistical Inference in Science ISBN: 0387950192 ISBN-13(EAN): 9780387950198 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A treatment of the problems of inference associated with experiments in science, with the emphasis on techniques for dividing the sample information into various parts, such that the diverse problems of inference that arise from repeatable experiments may be addressed.
Автор: Martin A. Tanner Название: Tools for Statistical Inference ISBN: 0387946888 ISBN-13(EAN): 9780387946887 Издательство: Springer Рейтинг: Цена: 93130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a unified introduction to a variety of computational algorithms for likelihood and Bayesian inference. The third edition expands the discussion of many of the techniques discussed, includes additional examples, and adds exercise sets at the end of each chapter.
Автор: D.A. Sprott Название: Statistical Inference in Science ISBN: 147577396X ISBN-13(EAN): 9781475773965 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A treatment of the problems of inference associated with experiments in science, with the emphasis on techniques for dividing the sample information into various parts, such that the diverse problems of inference that arise from repeatable experiments may be addressed.
Автор: Cheng Russell C H Название: Non-Standard Parametric Statistical Inference ISBN: 0198505043 ISBN-13(EAN): 9780198505044 Издательство: Oxford Academ Рейтинг: Цена: 129360.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This research monograph gives a unified view of non-standard estimation problems. It provides an overall mathematical framework, but also draws together and studies in detail a large number of practical problems, previously only treated separately, offering solution methods and numerical procedures for each.
Автор: Masanobu Taniguchi; Yoshihide Kakizawa Название: Asymptotic Theory of Statistical Inference for Time Series ISBN: 1461270286 ISBN-13(EAN): 9781461270287 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. A wide variety of stochastic processes, including non-Gaussian linear processes, long-memory processes, nonlinear processes, non-ergodic processes and diffusion processes are described.
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