Statistical Theory And Modelling
Download Statistical Theory And Modelling full books in PDF, epub, and Kindle. Read online free Statistical Theory And Modelling ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : D.V. Hinkley |
Publisher | : Chapman and Hall/CRC |
Total Pages | : 386 |
Release | : 1991 |
Genre | : Mathematics |
ISBN | : |
Statistical Theory and Modelling is a celebration of the work of Sir David Cox, FRS, and reflects his many interests in statistical theory and methods. It is a series of review articles, intended as an introduction to a variety of topics suitable for the graduate student and practicing statistician. Many of the topics are the subject of book-length treatments by Sir David and authors of this volume. Each chapter leads to a larger literature. Topics range the breadth of statistics and include modern degvelopments in statistical theory and methods. Special topics covered are generalized linear models, residuals and diagnostics, survival analysis, sequential analysis, time series, stochastic modelling of spatial data, design of experiments, likelihood inference and statistical approximation.
Author | : P. A. Durbin |
Publisher | : John Wiley & Sons |
Total Pages | : 347 |
Release | : 2011-06-28 |
Genre | : Science |
ISBN | : 1119957524 |
Providing a comprehensive grounding in the subject of turbulence, Statistical Theory and Modeling for Turbulent Flows develops both the physical insight and the mathematical framework needed to understand turbulent flow. Its scope enables the reader to become a knowledgeable user of turbulence models; it develops analytical tools for developers of predictive tools. Thoroughly revised and updated, this second edition includes a new fourth section covering DNS (direct numerical simulation), LES (large eddy simulation), DES (detached eddy simulation) and numerical aspects of eddy resolving simulation. In addition to its role as a guide for students, Statistical Theory and Modeling for Turbulent Flows also is a valuable reference for practicing engineers and scientists in computational and experimental fluid dynamics, who would like to broaden their understanding of fundamental issues in turbulence and how they relate to turbulence model implementation. Provides an excellent foundation to the fundamental theoretical concepts in turbulence. Features new and heavily revised material, including an entire new section on eddy resolving simulation. Includes new material on modeling laminar to turbulent transition. Written for students and practitioners in aeronautical and mechanical engineering, applied mathematics and the physical sciences. Accompanied by a website housing solutions to the problems within the book.
Author | : David A. Freedman |
Publisher | : Cambridge University Press |
Total Pages | : 459 |
Release | : 2009-04-27 |
Genre | : Mathematics |
ISBN | : 1139477315 |
This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
Author | : P. A. Durbin |
Publisher | : Wiley-Blackwell |
Total Pages | : 312 |
Release | : 2001-03-12 |
Genre | : Mathematics |
ISBN | : |
Most natural and industrial flows are turbulent. The atmosphere and oceans, automobile and aircraft engines, all provide examples of this ubiquitous phenomenon. In recent years, turbulence has become a very lively area of scientific research and application, and this work offers a grounding in the subject of turbulence, developing both the physical insight and the mathematical framework needed to express the theory. Providing a solid foundation in the key topics in turbulence, this valuable reference resource enables the reader to become a knowledgeable developer of predictive tools. This central and broad ranging topic would be of interest to graduate students in a broad range of subjects, including aeronautical and mechanical engineering, applied mathematics and the physical sciences. The accompanying solutions manual to the text also makes this a valuable teaching tool for lecturers and for practising engineers and scientists in computational and experimental and experimental fluid dynamics.
Author | : Jorma Rissanen |
Publisher | : Springer Science & Business Media |
Total Pages | : 145 |
Release | : 2007-12-15 |
Genre | : Mathematics |
ISBN | : 0387688129 |
No statistical model is "true" or "false," "right" or "wrong"; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial.
Author | : W. J. Krzanowski |
Publisher | : Wiley |
Total Pages | : 264 |
Release | : 2010-06-28 |
Genre | : Mathematics |
ISBN | : 9780470711019 |
Statisticians rely heavily on making models of 'causal situations' in order to fully explain and predict events. Modelling therefore plays a vital part in all applications of statistics and is a component of most undergraduate programmes. 'An Introduction to Statistical Modelling' provides a single reference with an applied slant that caters for all three years of a degree course. The book concentrates on core issues and only the most essential mathematical justifications are given in detail. Attention is firmly focused on the statistical aspects of the techniques, in this lively, practical approach.
Author | : William Kaye Estes |
Publisher | : Psychology Press |
Total Pages | : 180 |
Release | : 1991 |
Genre | : Psychology |
ISBN | : 9780805806885 |
First Published in 1991. Routledge is an imprint of Taylor & Francis, an informa company.
Author | : Rolf Sundberg |
Publisher | : Cambridge University Press |
Total Pages | : 297 |
Release | : 2019-08-29 |
Genre | : Business & Economics |
ISBN | : 1108476597 |
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.
Author | : Dirk P. Kroese |
Publisher | : Springer Science & Business Media |
Total Pages | : 412 |
Release | : 2013-11-18 |
Genre | : Computers |
ISBN | : 1461487757 |
This textbook on statistical modeling and statistical inference will assist advanced undergraduate and graduate students. Statistical Modeling and Computation provides a unique introduction to modern Statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of Mathematical Statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. Each of the three parts will cover topics essential to university courses. Part I covers the fundamentals of probability theory. In Part II, the authors introduce a wide variety of classical models that include, among others, linear regression and ANOVA models. In Part III, the authors address the statistical analysis and computation of various advanced models, such as generalized linear, state-space and Gaussian models. Particular attention is paid to fast Monte Carlo techniques for Bayesian inference on these models. Throughout the book the authors include a large number of illustrative examples and solved problems. The book also features a section with solutions, an appendix that serves as a MATLAB primer, and a mathematical supplement.
Author | : Stuart Coles |
Publisher | : Springer Science & Business Media |
Total Pages | : 219 |
Release | : 2013-11-27 |
Genre | : Mathematics |
ISBN | : 1447136756 |
Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.