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


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Автор: Hald Anders
Название:  A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935
Перевод названия: Андерс Хальд: История заключений параметрической статистики от Бернулли до Фишера, 1713-1930 гг.
ISBN: 9780387464084
Издательство: Springer
Классификация:

ISBN-10: 0387464085
Обложка/Формат: Hardback
Страницы: 240
Вес: 0.50 кг.
Дата издания: 29.12.2006
Серия: Sources and Studies in the History of Mathematics and Physical Sciences
Язык: English
Иллюстрации: 11 black & white illustrations, 1 black & white ta
Размер: 166 x 239 x 20
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
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.
Дополнительное описание: Формат: 235x155
Илюстрации: 11
Круг читателей: Students, researchers
Ключевые слова:
Язык: eng
Оглавление: Introduction.- The Three Revolutions in Parametric Statistical Inference.- James Bernoulli’s Law of Large Numbers for the Binomial, 1713, and its Generalization.- De Moivre's Normal Approximation to the Binomial, 1733, and its Generalizations.- Bayes's Posterior Distribution of the Binomial Parameter and His Rule for Inductive Inference, 1764.- Laplace’s Theory of Inverse Probability, 1774-1786.- A Nonprobabilistic Interlude: The Fitting of Equations to Data, 1750-1805.- Gauss’s Derivation of the Normal Distribution and the Method of Least Squares, 1809.- Credibility and Confidence Intervals by Laplace and Gauss.- The Multivariate Posterior Distribution.- Edgeworth’s Genuine Inverse Method and the Equivalence of Inverse and Direct Probability in Large Samples, 1908 and 1909.- Criticisms of Inverse Probability.- Laplace’s Central Limit Theorem and Linear Minimum Variance Estimation.- Gauss’s Theory of Linear Minimum Variance Estimation.- The Development of a Frequentist Error Theory.- Skew Distributions and the Method of Moments.- Normal Correlation and Regression.- Sampling Distributions Under Normality, 1876-1908.- Fisher's Early papers, 1912-1921.- The revolutionary paper, 1922.- Studentization, the F Distribution and the Analysis of Variance, 1922-1925.- The Likelihood Function, Ancillarity and Conditional Inference .- References.- Subject Index.- Author Index.



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.

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
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Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

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.


Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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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.

Topics on Methodological and Applied Statistical Inference

Автор: Di Battista
Название: Topics on Methodological and Applied Statistical Inference
ISBN: 3319440926 ISBN-13(EAN): 9783319440927
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book brings together selected peer-reviewed contributions from various research fields in statistics, and highlights the diverse approaches and analyses related to real-life phenomena.

New Developments in Statistical Modeling, Inference and Application

Автор: Jin
Название: New Developments in Statistical Modeling, Inference and Application
ISBN: 3319425706 ISBN-13(EAN): 9783319425702
Издательство: Springer
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Цена: 111790.00 T
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Описание: The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.

Statistical and Inductive Inference by Minimum Message Length

Автор: C.S. Wallace
Название: Statistical and Inductive Inference by Minimum Message Length
ISBN: 1441920153 ISBN-13(EAN): 9781441920157
Издательство: Springer
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Цена: 144410.00 T
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Описание: Mythanksareduetothemanypeoplewhohaveassistedintheworkreported here and in the preparation of this book. The work is incomplete and this account of it rougher than it might be. Such virtues as it has owe much to others; the faults are all mine. MyworkleadingtothisbookbeganwhenDavidBoultonandIattempted to develop a method for intrinsic classi?cation. Given data on a sample from some population, we aimed to discover whether the population should be considered to be a mixture of di?erent types, classes or species of thing, and, if so, how many classes were present, what each class looked like, and which things in the sample belonged to which class. I saw the problem as one of Bayesian inference, but with prior probability densities replaced by discrete probabilities re?ecting the precision to which the data would allow parameters to be estimated. Boulton, however, proposed that a classi?cation of the sample was a way of brie?y encoding the data: once each class was described and each thing assigned to a class, the data for a thing would be partially implied by the characteristics of its class, and hence require little further description. After some weeks arguing our cases, we decided on the maths for each approach, and soon discovered they gave essentially the same results. Without Boulton s insight, we may never have made the connection between inference and brief encoding, which is the heart of this work."

Bayesian inference in statistical analysis

Автор: Box, George E. P. Tiao, George C.
Название: Bayesian inference in statistical analysis
ISBN: 0471574287 ISBN-13(EAN): 9780471574286
Издательство: Wiley
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Цена: 169960.00 T
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Описание: Designed to form the basis of a graduate course on Bayesian inference, this textbook discusses important general issues of the Bayesian approach. It investigates problems, illustrating the appropriate analysis of mathematical results with numerical examples.

Introduction to Probability and Statistical Inference

Автор: Roussas George G
Название: Introduction to Probability and Statistical Inference
ISBN: 0128001143 ISBN-13(EAN): 9780128001141
Издательство: Elsevier Science
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Цена: 110030.00 T
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Описание:

An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help them obtain the best solution to a posed question or situation. It provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations.

This text contains an enhanced number of exercises and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities. Reorganized material is included in the statistical portion of the book to ensure continuity and enhance understanding. Each section includes relevant proofs where appropriate, followed by exercises with useful clues to their solutions. Furthermore, there are brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises are available to instructors in an Answers Manual.

This text will appeal to advanced undergraduate and graduate students, as well as researchers and practitioners in engineering, business, social sciences or agriculture.

Exact Statistical Inference for Categorical Data

Автор: Guogen Shan
Название: Exact Statistical Inference for Categorical Data
ISBN: 0081006810 ISBN-13(EAN): 9780081006818
Издательство: Elsevier Science
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Цена: 58380.00 T
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Описание:

Exact Statistical Inference for Categorical Data discusses the way asymptotic approaches have been often used in practice to make statistical inference. This book introduces both conditional and unconditional exact approaches for the data in 2 by 2, or 2 by k contingency tables, and is an ideal reference for users who are interested in having the convenience of applying asymptotic approaches, with less computational time. In addition to the existing conditional exact inference, some efficient, unconditional exact approaches could be used in data analysis to improve the performance of the testing procedure.

  • Demonstrates how exact inference can be used to analyze data in 2 by 2 tables
  • Discusses the analysis of data in 2 by k tables using exact inference
  • Explains how exact inference can be used in genetics

Statistical Inference in Finan cial and Insurance Mathematics with R

Автор: Brouste Alexandre
Название: Statistical Inference in Finan cial and Insurance Mathematics with R
ISBN: 1785480839 ISBN-13(EAN): 9781785480836
Издательство: Elsevier Science
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Цена: 150470.00 T
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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

Probability and statistical inference

Автор: Bartoszynski, Robert Niewiadomska-bugaj, Magdalena
Название: Probability and statistical inference
ISBN: 0471696935 ISBN-13(EAN): 9780471696933
Издательство: Wiley
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Цена: 152070.00 T
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Описание: Introduces probability and statistical concepts through non-trivial, real-world examples. This title promotes the development of intuition rather than simple application. Covering the advancements in computer-intensive methods, it provides the tools needed to develop an understanding of the theory of statistics and its probabilistic foundations.


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