Book Description
This text/reference provides a broad survey of aspects of model-building and statistical inference. Presents an accessible synthesis of current theoretical literature, requiring only familiarity with linear regression methods. The three chapters on central computational questions comprise a self-contained introduction to unconstrained optimization. Includes many illustrative practical examples.
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This text/reference provides a broad survey of aspects of model-building and statistical inference. Presents an accessible synthesis of current theoretical literature, requiring only familiarity with linear regression methods. The three chapters on central computational questions comprise a self-contained introduction to unconstrained optimization. Includes many illustrative practical examples.
Customer Reviews:
Good Text: Rigorous and Theoretical but Clear.......2007-01-09
I am a Chemist Phd working in the oil refining industry and often use statistical tools to model plant process and laboratory data. this text is not for practical uses but is to be considered a very rigorous and in depht introduction to nonlinear regression theory. Even if quite long and detailed is still clear and not difficult to understand. if you have time to devote to the principles and not jump to solutions this is a very good advanced text
excellent coverage by accomplished authors.......2001-05-05
I have recently reviewed for amazon the texts by Gallant and the one by Bates and Watts. This text was written by Seber and Wild, two accomplished statisticians and experienced authors. This volume is of the same high caliber as those texts and deserves mention. It is a longer text that overlaps on many topics with the other two books, deliberately neglects some areas that were well covered by Gallant (Gallant's book came out in 1987 and this one in 1989) and hits some topics not covered by either of the other two books.
Bootstrap methods are neglected probably because the value of the bootstrap for standard error estimation in nonlinear models was not yet appreciated in 1989.
Chapters 1 and 2 provide good introductory material similar to the other texts. Chapter 1 deals with the models (linear and nonlinear) and Chapter 2 provides the basic estimation techniques. In addition to the standard material on least squares, generalized least squares and maximum likelihood, the authors also cover quasi-likelihood, linear approximations, robust estimation and Bayesian methods. Box - Cox transformations and the issue of variance heterogeneity are also treated in Chapter 2.
As they remark in the preface, they avoid much of the econometric theory and asymptotic theory that is well covered in Gallant's book.
Chapter 3 deals with important practical issues including the convergence properties of the iterative procedures (important for nonlinear models but a non-issue in linear models), ill-conditioning and identifiability (important issues for both linear and nonlinear models).
Chapter 4 deals with curvature issues and covers much of the original work of Bates and Watts with many references to those authors. Oddly though, there is no mention of the Bates and Watts text. Both books were published by Wiley around the same time with Bates and Watts appearing in 1988 and Seber and Wild in 1989. Perhaps the Seber and Wild book went to the publisher before the Bates and Watts book came out (their preface has a May 1988 date).
Important and interesting topics covered in this book but not the others include models with time dependent errors, detailed treatment of growth models, compartmental models, multiphase and spline regresions and error-in-variables models. They also devote a whole chapter to software issues (very interesting and practical but probably mostly outdated).
Good for a graduate statistics course or for a research reference source. Has lots of material and references but lacks homework problems.
Excelent book on nonlinear regression!.......2000-04-05
This book covers the whole theory of nonlinear regression. I think it is essential both for students of statistics and for scientists, not only as a study book but also as a reference book. I recommend it to those who already have had an introductory course on the subject and need to go deeper into it.
Book Description
It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available. What's new in the Second Edition? · Greatly expanded discussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques · A new chapter on longitudinal data and mixed models · A thoroughly revised chapter on nonparametric regression and density estimation · A totally new chapter on semiparametric regression · Survival analysis expanded into its own separate chapter · Completely rewritten chapter on score functions · Many more examples and illustrative graphs · Unique data sets compiled and made available online In addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you're looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition is your ideal source.
Customer Reviews:
excellent coverage of special nonlinear models.......2000-08-10
Ray Carroll and David Ruppert are well known research statisticians who have published many joint articles on regression, weighted regression and transformation and they have also written an excellent book together on this research topic. Stefanski has recently published several papers on measurement error models with Carroll. Here they have teamed up to write a statistics text on a unique topic. Measurement error models are common and practical when dealing with covariates that have measurement error. Least squares estimation in linear regression is based on the assumption that the predictor variables are measured without error. There are many articles and an excellent text by Fuller "Measurement Error Models", published by Wiley in 1988 that deals with the linear case. Also look at a section in Chapter 5 of Miller's "Beyond ANOVA, Basics of Applied Statistics" that refers to the problem as the error in variables problem. For the nonlinear case this is the first treatment. Well written and well documented, this text provides an up-to-date account of the theory and methods and provides real applications (e.g. the Framingham Heart Study). This is a great reference as are many of the other monographs in this series by Chapman and Hall/CRC Press. Includes bootstrap approaches in the chapter on fitting methods and models.
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Design Analysis: Mathematical Modeling of Nonlinear Systems
David E. Thompson
Manufacturer: Cambridge University Press
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Mathematical Modeling for Industry and Engineering
ASIN: 0521621704 |
Book Description
An integral part of engineering design is the development of models that describe physical behavior or phenomena in mathematical terms. As engineering systems have become more complex, classic linear methods of modeling and analysis have proved inadequate, creating a need for nonlinear models to solve design problems. This text provides an introduction to mathematical modeling of linear and nonlinear systems, with an emphasis on the solution of nonlinear design problems. While encouraging the use of the computer as a tool for modeling and analysis, the aim is to discuss the basic concepts underlying computer techniques and to seek analytical solutions. Among topics covered are exact solution, numerical solution, graphical solution, and approximate solution methods; and the stability of nonlinear systems. Numerous examples show how to apply modeling methods to real engineering systems. The book also includes end-of-chapter problems and case studies of challenging design problems. Intended for senior or beginning graduate students, this text will also serve as a helpful reference for practicing engineers.
Book Description
A revised collection of groundbreaking presentations made at a recent IMS (International Microwave Symposium) workshop, this cutting-edge resource provides a comprehensive treatment of nonlinear behavioral modeling for RF and microwave circuits and systems from renowned experts in the field. Presenting state-of-the-art RF and microwave applications, this practical book gives you hands-on techniques that you can use immediately on your current projects.
The book helps you create nonlinear behavioral models in the frequency and time domain, as well as in the envelope domain for wireless applications. You learn how to make large-signal microwave measurements for nonlinear model extraction and gain a thorough understanding of the use of neural networks in nonlinear behavioral model generation. Moreover, this unique reference explains the physical mechanisms responsible for dynamic nonlinear effects in microwave ICs, such as memory in power amplifiers. Other key topics discussed in detail include Volterra analysis, scattering functions, envelope models, and the application of neural networks.
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Managing Emergent Phenomena: Nonlinear Dynamics in Work Organizations
Stephen J. Guastello
Manufacturer: Lawrence Erlbaum
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Sync: The Emerging Science of Spontaneous Order
ASIN: 0805831630 |
Book Description
Chaos, catastrophe, self-organization, and complexity theories (nonlinear dynamics) now have practical and measurable roles in the functioning of work organizations. Managing Emergent Phenomena begins by describing how the concept of an organization has changed from a bureaucracy, to a humanistic and organic system, to a complex adaptive system. The dynamics concepts are then explained along with the most recent research methods for analyzing real data. Applications include: work motivation, personnel selection and turnover, creative thinking by individuals and groups, the development of social networks, coordination in work groups, the emergence of leaders, work performance in organizational hierarchies, economic problems that are relevant to organizations, techniques for predicting the future, and emergency management.
Each application begins with a tight summary of standard thinking on a subject, followed by the new insights that are afforded by nonlinear dynamics and the empirical data supporting those ideas. Unusual concepts are also encountered, such as the organizational unconscious, collective intelligence, and the revolt of the slaved variables. The net results are a new perspective on what is really important in organizational life, original insights on familiar experiences, and some clear signposts for the next generation of nonlinear social scientists.
Book Description
Divorce rates are at an all-time high. But without a theoretical understanding of the processes related to marital stability and dissolution, it is difficult to design and evaluate new marriage interventions. The Mathematics of Marriage provides the foundation for a scientific theory of marital relations. The book does not rely on metaphors, but develops and applies a mathematical model using difference equations. The work is the fulfillment of the goal to build a mathematical framework for the general system theory of families first suggested by Ludwig Von Bertalanffy in the 1960s.
The book also presents a complete introduction to the mathematics involved in theory building and testing, and details the development of experiments and models. In one "marriage experiment," for example, the authors explored the effects of lowering or raising a couple�s heart rates. Armed with their mathematical model, they were able to do real experiments to determine which processes were affected by their interventions.
Applying ideas such as phase space, null clines, influence functions, inertia, and uninfluenced and influenced stable steady states (attractors), the authors show how other researchers can use the methods to weigh their own data with positive and negative weights. While the focus is on modeling marriage, the techniques can be applied to other types of psychological phenomena as well.
Customer Reviews:
mixed.......2007-01-20
Chapter 2 with an overview of marriage research was fascinating. Chapters 3-8 with a discussion of non-linear modeling and catastrophe theory were very clear.
The sections applying the non-linear modeling to marriage interactions were less convincing. Part of the problem is that each non-linear model concerns a single discussion rather than the state of a marriage as a whole. A marriage with two steady states is one thing; a conversation with two steady states is something else.
Gottman's previous work has found that the ratio of positive to negative interactions in a single marriage discussion can strongly predict whether the married couples will divorce. Couples with a good marriages had an average of a 5 to 1 positive/negative ratio while couples that ended up divorcing had an average of a 0.8 to 1 positive/negative ratio. Not surprisingly, the parameters of the functions of the nonlinear models were also different between the divorcing and the happily married couples, but it isn't clear that the additional complexity gets the authors much, if any, analytical benefit.
Excellent!.......2006-08-08
I love John Gottman's work and I assign him regularily to my students. His work on partnership processes has always been first-rate and this book is no exception. Don't let the math scare you--it is an interesting read, indeed!
Excellent, but for two different purposes.......2006-01-14
This book has an excellent introduction to model building; one of the best I have ever read. Starts with easy math and college stuff you probably forgot much of, then shows how to do great and unexpected things with it. You dont have to know all the math to see how powerful it can be for exploring any relation: man:woman, customer:seller, investor:company. What attracts them, engages them and holds them. When it doesnt work, why not. The other use? People who want to understand better why marriages work or dont. The findings the authors made are here. You dont need to know or even read the math parts to be able to use the findings, which are new and powerful. Certainly worth $28 bucks and a read.
Hilarious.......2003-05-02
This book offers common sense for marriages, but now it adds math. If both partners have the mathematics background and enjoy complex equations, this book is worth the value in entertainment. Modelling your marriage is just plain goofy, which adds to the novelty of this book.
If you don't enjoy sitting down and going through a math book doing the problems and setting up equations, this is not the book for you.
Product Description
An insightful, comprehensive, and up-to-date treatment of linear, nonlinear, and discrete/combinatorial network optimization problems, their applications, and their analytical and algorithmic methodology. It covers extensively theory, algorithms, and applications, and it aims to bridge the gap between linear and nonlinear network optimization on one hand, and integer/combinatorial network optimization on the other. Among its special features, the book: 1) provides a comprehensive account of the principal algorithms for linear network flow problems, including simplex, dual ascent, and auction algorithms 2) describes the application of network algorithms in many practical contexts, with special emphasis on data communication networks 3) develops in detail the computational complexity analysis of the main linear network optimization algorithms 4) covers extensively the main algorithms for specialized network problems, such as shortest path, max-flow, assignment, and traveling salesman 5) describes the main models for discrete network optimization problems, such as constrained shortest path, traveling salesman, vehicle routing, multidimensional assignment, facility location, spanning tree construction, etc 6) describes the main algorithmic approaches for integer-constrained network problems, such as branch-and-bound, Lagrangian relaxation and subgradient optimization, genetic algorithms, tabu search, simulated annealing, and rollout algorithms 7) develops the main methods for nonlinear network problems, such as convex separable and multicommodity flow problems arising in communication, transportation, and manufacturing contexts 8) discusses extensively auction algorithms, based on the author's original research on the subject 9) contains many examples, practical applications, illustrations, and exercises 10) contains much new material not found in any other textbook
Customer Reviews:
Challenging & Succesful Treatment of the Subject.......2001-09-27
Bertsakas's Network Optimization is probably the most challenging graduate textbook on network flows and optimization. Besides the chapters on classical subjects as shortest path or max-flow/min-cost problems, (which are very rigorously dealt despite their very standard nature of the subjects) I've found especially the Auction Algorithms chapter very throughout and inspiring. The next chapters, Nonlinear Network Optimization and Network Problems with Integer Constraints also are good; these are not usually included in other graduate network optimization books. In each chapter, Author digs into almost all theorems, propositions or notions and don't miss the related proofs or demonstrations, which is usually omitted in other books. I guess it is an important feature for those who want to see theoretical background of the subjects. Its bibliography is very rich and sufficiently up-to-date (until 1997, not bad since it is printed at 1998!). I've found the exercises very challenging, one should consume a very lot of time to do the necessary proofs. These are not as numerous as in Bazaraa's or Ahuja's books, but their quality is by far superior; the author hasn't filled the book with the standard/classical exercises which can be found in all books. Since it deals in detail with the theory, the presentation of the subjects sometimes appears difficult to capture. I also advise to get the errata from book's homepage since it may create sometimes difficulties. The graph theory notions come usually omitted in the book, so one may need a graph theory title to accompany it. Also its appendix that contains a mathematical review somewhat less extensive than in his "Nonlinear Programming" book (almost a separate monograph!), which I recommend highly also. Thus the book comes devoted and concentrated solely on the Network Optimization theory and algorithms, and in my opinion, it became highly successful. I strongly believe that may become the standard title on the subject of the following years. For those who may find its presentation difficult, I suggest to use it along with Ahuja's "Network Flows" which has a more general structure and presentation. But I found the book clearly superior to that book or Bazaraa's "Linear Programming and Network Flows" whose Network Flows chapters are messy. Finally I may say, it is a highly successful book is very worth of its price.
Lucid, well-illustrated study of network flows.......2000-12-22
This is a well-explained, well-illustrated introduction of some of the most important aspects of network flows. (Note: This is an Internet-centric review, even though the book is not about the Internet.) Although the treatment is theoretical rather than specific to the Internet, it is especially relevant now that traffic engineering is being applied to the Internet. Of course ATM and telephone networks have employed this for many years, but there is a need to go back to fundamentals when applying these concepts to the Internet (or other areas). The book starts with the shortest path problem, which is familiar to the Internet community. Then max-flow and min-cost problems are introduced. These are central to traffic engineering. Thereafter non-linear network flow optimization and discrete problems are attacked. Linear programming techniques such as the simplex method are also described. Is excellent training material for those having to wrestle with traffic engineering problems.
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Linear And Nonlinear Models: Fixed Effects, Random Effects, And Mixed Models
Erik W. Grafarend
Manufacturer: Walter de Gruyter
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ASIN: 3110162164 |
Product Description
This monograph contains a thorough treatment of methods for solving over- and underdetermined systems of equations, e.g. the minimum norm solution method with respect to weighted norms. The considered equations can be nonlinear or linear, and deterministic models as well as probabilistic ones are considered. An extensive appendix provides all necessary prerequisites like matrix algebra, matrix analysis and Lagrange multipliers, and a long list of references is also included.
Book Description
This unique new book is your single resource for all issues related to intermodulation and multi-tone distortion in microwave and wireless circuits. Beginning with an overview of the general concepts of distortion in microwave and wireless devices, it delves into the theory and practical aspects of nonlinear distortion, tools for nonlinear analysis, mathematical representations of wireless circuits and devices, and design methods for minimizing distortion.
The book presents the full range of distortion specs to help ensure you select the right telecommunications equipment for your needs. Choose from the full range of design methods for highly linear circuits to optimize linearity in small-signal and high-power amplifiers and mixers. Practical advice on modeling and computer-aided tools guides you toward successful analysis and design. Moreover, the book helps you design other highly-linear circuits and systems related to microwave and wireless communications and it includes the most comprehensive treatment of the application of Volterra methods in the technical literature.
Book Description
This edited volume gives a new and integrated introduction to item response models (predominantly used in measurement applications in psychology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. The new framework allows the domain of item response models to be co-ordinated and broadened to emphasize their explanatory uses beyond their standard descriptive uses.
The basic explanatory principle is that item responses can be modeled as a function of predictors of various kinds. The predictors can be (a) characteristics of items, of persons, and of combinations of persons and items; (b) observed or latent (of either items or persons); and they can be (c) latent continuous or latent categorical. In this way a broad range of models is generated, including a wide range of extant item response models as well as some new ones. Within this range, models with explanatory predictors are given special attention in this book, but we also discuss descriptive models. Note that the term "item responses" does not just refer to the traditional "test data," but are broadly conceived as categorical data from a repeated observations design. Hence, data from studies with repeated observations experimental designs, or with longitudinal designs, may also be modelled.
The book starts with a four-chapter section containing an introduction to the framework. The remaining chapters describe models for ordered-category data, multilevel models, models for differential item functioning, multidimensional models, models for local item dependency, and mixture models. It also includes a chapter on the statistical background and one on useful software. In order to make the task easier for the reader, a unified approach to notation and model description is followed throughout the chapters, and a single data set is used in most examples to make it easier to see how the many models are related. For all major examples, computer commands from the SAS package are provided that can be used to estimate the results for each model. In addition, sample commands are provided for other major computer packages.
Paul De Boeck is Professor of Psychology at K.U. Leuven (Belgium), and Mark Wilson is Professor of Education at UC Berkeley (USA). They are also co-editors (along with Pamela Moss) of a new journal entitled Measurement: Interdisciplinary Research and Perspectives. The chapter authors are members of a collaborative group of psychometricians and statisticians centered on K.U. Leuven and UC Berkeley.
From the reviews:
"[It is] full of nice features to make it widely useable by practitioners and applied statisticians alike, and it does a wonderful job connecting psychometrics to the field of statisitcs." Deniz Senturk for Technometrics, November 2006
"This book seeks to generalize the typical perspective on item response models, putting the ideas into a broader statistical context. … The authors have made a good job of integrating the various contributions, and I believe the book will help in increasing awareness of the potential of these types of models." (D.J.Hand, Short Book Reviews Publication of the International Statistical Institute, Vol. 25 (1), 2005)
Books:
- Numerical Methods in Economics
- Numerical Methods in Finance and Economics: A MATLAB-Based Introduction (Statistics in Practice)
- One-Handed in a Two-Handed World (Second Edition)
- Optoelectronics: An Introduction (3rd Edition)
- Pilgrim at Tinker Creek
- PowerNomics : The National Plan to Empower Black America
- Private Capital Markets: Valuation, Capitalization, and Transfer of Private Business Interests
- Private Warriors
- Privatization and Public-Private Partnerships
- Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers
Books Index
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