The Theory Of Inference

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The Limits of Inference without Theory

Author : Kenneth I. Wolpin
Publisher : MIT Press
ISBN 13 : 0262019086
Total Pages : 197 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Limits of Inference without Theory by : Kenneth I. Wolpin

Download or read book The Limits of Inference without Theory written by Kenneth I. Wolpin and published by MIT Press. This book was released on 2013-04-26 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The role of theory in ex ante policy evaluations and the limits that eschewing theory places on inference In this rigorous and well-crafted work, Kenneth Wolpin examines the role of theory in inferential empirical work in economics and the social sciences in general—that is, any research that uses raw data to go beyond the mere statement of fact or the tabulation of statistics. He considers in particular the limits that eschewing the use of theory places on inference. Wolpin finds that the absence of theory in inferential work that addresses microeconomic issues is pervasive. That theory is unnecessary for inference is exemplified by the expression “let the data speak for themselves.” This approach is often called “reduced form.” A more nuanced view is based on the use of experiments or quasi-experiments to draw inferences. Atheoretical approaches stand in contrast to what is known as the structuralist approach, which requires that a researcher specify an explicit model of economic behavior—that is, a theory. Wolpin offers a rigorous examination of both structuralist and nonstructuralist approaches. He first considers ex ante policy evaluation, highlighting the role of theory in the implementation of parametric and nonparametric estimation strategies. He illustrates these strategies with two examples, a wage tax and a school attendance subsidy, and summarizes the results from applications. He then presents a number of examples that illustrate the limits of inference without theory: the effect of unemployment benefits on unemployment duration; the effect of public welfare on women's labor market and demographic outcomes; the effect of school attainment on earnings; and a famous field experiment in education dealing with class size. Placing each example within the context of the broader literature, he contrasts them to recent work that relies on theory for inference.

Statistical Theory and Inference

Author : David J. Olive
Publisher : Springer
ISBN 13 : 3319049720
Total Pages : 434 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Statistical Theory and Inference by : David J. Olive

Download or read book Statistical Theory and Inference written by David J. Olive and published by Springer. This book was released on 2014-05-07 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.

Information Theory, Inference and Learning Algorithms

Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Information Theory, Inference and Learning Algorithms by : David J. C. MacKay

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents

Introduction to the Theory of Statistical Inference

Author : Hannelore Liero
Publisher : CRC Press
ISBN 13 : 1466503203
Total Pages : 280 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Introduction to the Theory of Statistical Inference by : Hannelore Liero

Download or read book Introduction to the Theory of Statistical Inference written by Hannelore Liero and published by CRC Press. This book was released on 2016-04-19 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the authors' lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models. Suitable for a second semester undergraduate course on statistical inference, the text offers proofs to support the mathematics and does not require any use of measure theory. It illustrates core concepts using cartoons and provides solutions to all examples and problems.

Unifying Political Methodology

Author : Gary King
Publisher : University of Michigan Press
ISBN 13 : 9780472085545
Total Pages : 290 pages
Book Rating : 4.0/5 (855 download)

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Book Synopsis Unifying Political Methodology by : Gary King

Download or read book Unifying Political Methodology written by Gary King and published by University of Michigan Press. This book was released on 1998-06-24 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: DIVArgues that likelihood theory is a unifying approach to statistical modeling in political science /div

Asymptotic Theory of Statistical Inference for Time Series

Author : Masanobu Taniguchi
Publisher : Springer Science & Business Media
ISBN 13 : 146121162X
Total Pages : 671 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Asymptotic Theory of Statistical Inference for Time Series by : Masanobu Taniguchi

Download or read book Asymptotic Theory of Statistical Inference for Time Series written by Masanobu Taniguchi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual AR, MA, and ARMA 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. The authors discuss estimation and testing theory and many other relevant statistical methods and techniques.

The Theory of Inference

Author : Henry Hughes
Publisher :
ISBN 13 :
Total Pages : 280 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis The Theory of Inference by : Henry Hughes

Download or read book The Theory of Inference written by Henry Hughes and published by . This book was released on 1894 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Theory of Statistical Inference

Author : Anthony Almudevar
Publisher : CRC Press
ISBN 13 : 1000488012
Total Pages : 470 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Theory of Statistical Inference by : Anthony Almudevar

Download or read book Theory of Statistical Inference written by Anthony Almudevar and published by CRC Press. This book was released on 2021-12-30 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory of Statistical Inference is designed as a reference on statistical inference for researchers and students at the graduate or advanced undergraduate level. It presents a unified treatment of the foundational ideas of modern statistical inference, and would be suitable for a core course in a graduate program in statistics or biostatistics. The emphasis is on the application of mathematical theory to the problem of inference, leading to an optimization theory allowing the choice of those statistical methods yielding the most efficient use of data. The book shows how a small number of key concepts, such as sufficiency, invariance, stochastic ordering, decision theory and vector space algebra play a recurring and unifying role. The volume can be divided into four sections. Part I provides a review of the required distribution theory. Part II introduces the problem of statistical inference. This includes the definitions of the exponential family, invariant and Bayesian models. Basic concepts of estimation, confidence intervals and hypothesis testing are introduced here. Part III constitutes the core of the volume, presenting a formal theory of statistical inference. Beginning with decision theory, this section then covers uniformly minimum variance unbiased (UMVU) estimation, minimum risk equivariant (MRE) estimation and the Neyman-Pearson test. Finally, Part IV introduces large sample theory. This section begins with stochastic limit theorems, the δ-method, the Bahadur representation theorem for sample quantiles, large sample U-estimation, the Cramér-Rao lower bound and asymptotic efficiency. A separate chapter is then devoted to estimating equation methods. The volume ends with a detailed development of large sample hypothesis testing, based on the likelihood ratio test (LRT), Rao score test and the Wald test. Features This volume includes treatment of linear and nonlinear regression models, ANOVA models, generalized linear models (GLM) and generalized estimating equations (GEE). An introduction to decision theory (including risk, admissibility, classification, Bayes and minimax decision rules) is presented. The importance of this sometimes overlooked topic to statistical methodology is emphasized. The volume emphasizes throughout the important role that can be played by group theory and invariance in statistical inference. Nonparametric (rank-based) methods are derived by the same principles used for parametric models and are therefore presented as solutions to well-defined mathematical problems, rather than as robust heuristic alternatives to parametric methods. Each chapter ends with a set of theoretical and applied exercises integrated with the main text. Problems involving R programming are included. Appendices summarize the necessary background in analysis, matrix algebra and group theory.

Models for Probability and Statistical Inference

Author : James H. Stapleton
Publisher : John Wiley & Sons
ISBN 13 : 0470183403
Total Pages : 466 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Models for Probability and Statistical Inference by : James H. Stapleton

Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

The Theory of Inference

Author : Hughes Henry
Publisher : Hardpress Publishing
ISBN 13 : 9781314520873
Total Pages : 286 pages
Book Rating : 4.5/5 (28 download)

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Book Synopsis The Theory of Inference by : Hughes Henry

Download or read book The Theory of Inference written by Hughes Henry and published by Hardpress Publishing. This book was released on 2013-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlike some other reproductions of classic texts (1) We have not used OCR(Optical Character Recognition), as this leads to bad quality books with introduced typos. (2) In books where there are images such as portraits, maps, sketches etc We have endeavoured to keep the quality of these images, so they represent accurately the original artefact. Although occasionally there may be certain imperfections with these old texts, we feel they deserve to be made available for future generations to enjoy.

Asymptotic Theory of Statistical Inference

Author : B. L. S. Prakasa Rao
Publisher :
ISBN 13 :
Total Pages : 458 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Asymptotic Theory of Statistical Inference by : B. L. S. Prakasa Rao

Download or read book Asymptotic Theory of Statistical Inference written by B. L. S. Prakasa Rao and published by . This book was released on 1987-01-16 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and stochastic processes; Limit theorems for some statistics; Asymptotic theory of estimation; Linear parametric inference; Martingale approach to inference; Inference in nonlinear regression; Von mises functionals; Empirical characteristic function and its applications.

Inference on the Low Level

Author : Hannes Leitgeb
Publisher : Springer Science & Business Media
ISBN 13 : 1402028067
Total Pages : 376 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Inference on the Low Level by : Hannes Leitgeb

Download or read book Inference on the Low Level written by Hannes Leitgeb and published by Springer Science & Business Media. This book was released on 2012-11-02 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: In contrast to the prevailing tradition in epistemology, the focus in this book is on low-level inferences, i.e., those inferences that we are usually not consciously aware of and that we share with the cat nearby which infers that the bird which she sees picking grains from the dirt, is able to fly. Presumably, such inferences are not generated by explicit logical reasoning, but logical methods can be used to describe and analyze such inferences. Part 1 gives a purely system-theoretic explication of belief and inference. Part 2 adds a reliabilist theory of justification for inference, with a qualitative notion of reliability being employed. Part 3 recalls and extends various systems of deductive and nonmonotonic logic and thereby explains the semantics of absolute and high reliability. In Part 4 it is proven that qualitative neural networks are able to draw justified deductive and nonmonotonic inferences on the basis of distributed representations. This is derived from a soundness/completeness theorem with regard to cognitive semantics of nonmonotonic reasoning. The appendix extends the theory both logically and ontologically, and relates it to A. Goldman's reliability account of justified belief.

Statistical Inference

Author : George Casella
Publisher : CRC Press
ISBN 13 : 1040024025
Total Pages : 1746 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Statistical Inference by : George Casella

Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 1746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.

Pattern Theory

Author : Ulf Grenander
Publisher : Oxford University Press
ISBN 13 : 0198505701
Total Pages : 633 pages
Book Rating : 4.1/5 (985 download)

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Book Synopsis Pattern Theory by : Ulf Grenander

Download or read book Pattern Theory written by Ulf Grenander and published by Oxford University Press. This book was released on 2007 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Pattern Theory' provides a comprehensice & accessible overview of the modern challenges in signal, data & pattern analysis in speech recognition, computational linguistics, image analysis & computer vision. Aimed at graduate students the text includes numerous exercises & an extensive bibliography.

The Theory of Inference

Author : Henry Hughes
Publisher :
ISBN 13 :
Total Pages : 284 pages
Book Rating : 4.:/5 (39 download)

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Book Synopsis The Theory of Inference by : Henry Hughes

Download or read book The Theory of Inference written by Henry Hughes and published by . This book was released on 1894 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Essential Statistical Inference

Author : Dennis D. Boos
Publisher : Springer Science & Business Media
ISBN 13 : 1461448182
Total Pages : 567 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Essential Statistical Inference by : Dennis D. Boos

Download or read book Essential Statistical Inference written by Dennis D. Boos and published by Springer Science & Business Media. This book was released on 2013-02-06 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.

Inference to the Best Explanation

Author : Peter Lipton
Publisher : Taylor & Francis
ISBN 13 : 9780415242035
Total Pages : 236 pages
Book Rating : 4.2/5 (42 download)

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Book Synopsis Inference to the Best Explanation by : Peter Lipton

Download or read book Inference to the Best Explanation written by Peter Lipton and published by Taylor & Francis. This book was released on 2004 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.