Author: Yudi Pawitan
Publisher: OUP Oxford
ISBN: 0191650587
Category : Mathematics
Languages : en
Pages : 626
Book Description
Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept ot the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from a simile comparison of two accident rates, to complex studies that require generalised linear or semiparametric modelling. The emphasis is that the likelihood is not simply a device to produce an estimate, but an important tool for modelling. The book generally takes an informal approach, where most important results are established using heuristic arguments and motivated with realistic examples. With the currently available computing power, examples are not contrived to allow a closed analytical solution, and the book can concentrate on the statistical aspects of the data modelling. In addition to classical likelihood theory, the book covers many modern topics such as generalized linear models and mixed models, non parametric smoothing, robustness, the EM algorithm and empirical likelihood.
Empirical Likelihood
Author: Art B. Owen
Publisher: CRC Press
ISBN: 1420036157
Category : Mathematics
Languages : en
Pages : 322
Book Description
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It al
Publisher: CRC Press
ISBN: 1420036157
Category : Mathematics
Languages : en
Pages : 322
Book Description
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It al
Statistical Evidence
Author: Richard Royall
Publisher: Routledge
ISBN: 1351414569
Category : Mathematics
Languages : en
Pages : 191
Book Description
Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.
Publisher: Routledge
ISBN: 1351414569
Category : Mathematics
Languages : en
Pages : 191
Book Description
Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.
Maximum Likelihood Estimation and Inference
Author: Russell B. Millar
Publisher: John Wiley & Sons
ISBN: 1119977711
Category : Mathematics
Languages : en
Pages : 286
Book Description
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.
Publisher: John Wiley & Sons
ISBN: 1119977711
Category : Mathematics
Languages : en
Pages : 286
Book Description
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.
Maximum Likelihood for Social Science
Author: Michael D. Ward
Publisher: Cambridge University Press
ISBN: 1107185823
Category : Political Science
Languages : en
Pages : 327
Book Description
Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation.
Publisher: Cambridge University Press
ISBN: 1107185823
Category : Political Science
Languages : en
Pages : 327
Book Description
Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation.
Probability, Statistics, and Truth
Author: Richard Von Mises
Publisher: Courier Corporation
ISBN: 0486242145
Category : Mathematics
Languages : en
Pages : 273
Book Description
This comprehensive study of probability considers the approaches of Pascal, Laplace, Poisson, and others. It also discusses Laws of Large Numbers, the theory of errors, and other relevant topics.
Publisher: Courier Corporation
ISBN: 0486242145
Category : Mathematics
Languages : en
Pages : 273
Book Description
This comprehensive study of probability considers the approaches of Pascal, Laplace, Poisson, and others. It also discusses Laws of Large Numbers, the theory of errors, and other relevant topics.
Confidence, Likelihood, Probability
Author: Tore Schweder
Publisher: Cambridge University Press
ISBN: 0521861608
Category : Business & Economics
Languages : en
Pages : 521
Book Description
This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.
Publisher: Cambridge University Press
ISBN: 0521861608
Category : Business & Economics
Languages : en
Pages : 521
Book Description
This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.
Drug-Induced Liver Injury
Author:
Publisher: Academic Press
ISBN: 0128173173
Category : Medical
Languages : en
Pages : 290
Book Description
Drug-Induced Liver Injury, Volume 85, the newest volume in the Advances in Pharmacology series, presents a variety of chapters from the best authors in the field. Chapters in this new release include Cell death mechanisms in DILI, Mitochondria in DILI, Primary hepatocytes and their cultures for the testing of drug-induced liver injury, MetaHeps an alternate approach to identify IDILI, Autophagy and DILI, Biomarkers and DILI, Regeneration and DILI, Drug-induced liver injury in obesity and nonalcoholic fatty liver disease, Mechanisms of Idiosyncratic Drug-Induced Liver Injury, the Evaluation and Treatment of Acetaminophen Toxicity, and much more. - Includes the authority and expertise of leading contributors in pharmacology - Presents the latest release in the Advances in Pharmacology series
Publisher: Academic Press
ISBN: 0128173173
Category : Medical
Languages : en
Pages : 290
Book Description
Drug-Induced Liver Injury, Volume 85, the newest volume in the Advances in Pharmacology series, presents a variety of chapters from the best authors in the field. Chapters in this new release include Cell death mechanisms in DILI, Mitochondria in DILI, Primary hepatocytes and their cultures for the testing of drug-induced liver injury, MetaHeps an alternate approach to identify IDILI, Autophagy and DILI, Biomarkers and DILI, Regeneration and DILI, Drug-induced liver injury in obesity and nonalcoholic fatty liver disease, Mechanisms of Idiosyncratic Drug-Induced Liver Injury, the Evaluation and Treatment of Acetaminophen Toxicity, and much more. - Includes the authority and expertise of leading contributors in pharmacology - Presents the latest release in the Advances in Pharmacology series