Download or read book Statistical Methods of Model Building Nonlinear regression functional relations and robust methods written by and published by . This book was released on 1900 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear Regression Functional Relations and Robust Methods written by Helga Bunke and published by Wiley. This book was released on 1989-11-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear Regression Functional Relations and Robust Methods written by Helga Bunke and published by . This book was released on 1989 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, the second volume in a three part work, provides a comprehensive and unified account of nonlinear regression analysis, functional and structural relations, and of nonparametric and robust estimators. Research in these areas has been stimulated by the increase in computational capabilities and this volume will therefore be of great interest to researchers in statistics as well as applied statisticians working in industry. The material provided includes recent work from German and Russian sources, as well as from English-speaking sources, and the treatment throughout is mathematically rigorous but accessible. The text will benefit rsearchers in statistics and applied statisticians working in industry.
Download or read book Statistical Methods of Model Building Nonlinear regression functional relations and robust methods written by Helga Bunke and published by . This book was released on 1986 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Methods of Model Building written by Helga Bunke and published by . This book was released on 1986 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Download or read book Robust Statistical Procedures written by Jana Jurecková and published by John Wiley & Sons. This book was released on 1996-04-19 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad and unified methodology for robust statistics—with exciting new applications Robust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the more diverse and sometimes confounding areas, given the many different assessments and interpretations of robustness by theoretical and applied statisticians. This innovative book unifies the many varied, yet related, concepts of robust statistics under a sound theoretical modulation. It seamlessly integrates asymptotics and interrelations, and provides statisticians with an effective system for dealing with the interrelations between the various classes of procedures. Drawing on the expertise of researchers from around the world, and covering over a decade's worth of developments in the field, Robust Statistical Procedures: Asymptotics and Interrelations: Discusses both theory and applications in its two parts, from the fundamentals to robust statistical inference Thoroughly explores the interrelations between diverse classes of procedures, unlike any other book Compares nonparametric procedures with robust statistics, explaining in detail asymptotic representations for various estimators Provides a timesaving list of mathematical tools for the problems under discussion Keeps mathematical abstractions to a minimum, in spite of its largely theoretical content Includes useful problems and exercises at the end of each chapter Offers strategies for more complex models when using robust statistical procedures Self-contained and rounded in approach, this book is invaluable for both applied statisticians and theoretical researchers; for graduate students in mathematical statistics; and for anyone interested in the influence of this methodology.
Download or read book Biostatistical Methods written by John M. Lachin and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive coverage of classical and modern methods of biostatistics Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathematical statistical tools and more modern likelihood-based theories. The first half of the book presents methods for the analysis of single and multiple 2x2 tables for cross-sectional, prospective, and retrospective (case-control) sampling, with and without matching using fixed and two-stage random effects models. The text then moves on to present a more modern likelihood- or model-based approach, which includes unconditional and conditional logistic regression; the analysis of count data and the Poisson regression model; and the analysis of event time data, including the proportional hazards and multiplicative intensity models. The book contains a technical appendix that presents the core mathematical statistical theory used for the development of classical and modern statistical methods. Biostatistical Methods: The Assessment of Relative Risks: * Presents modern biostatistical methods that are generalizations of the classical methods discussed * Emphasizes derivations, not just cookbook methods * Provides copious reference citations for further reading * Includes extensive problem sets * Employs case studies to illustrate application of methods * Illustrates all methods using the Statistical Analysis System(r) (SAS) Supplemented with numerous graphs, charts, and tables as well as a Web site for larger data sets and exercises, Biostatistical Methods: The Assessment of Relative Risks is an excellent guide for graduate-level students in biostatistics and an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.
Download or read book Simulation written by James R. Thompson and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique, integrated treatment of computer modeling and simulation "The future of science belongs to those willing to make the shift to simulation-based modeling," predicts Rice Professor James Thompson, a leading modeler and computational statistician widely known for his original ideas and engaging style. He discusses methods, available to anyone with a fast desktop computer, for integrating simulation into the modeling process in order to create meaningful models of real phenomena. Drawing from a wealth of experience, he gives examples from trading markets, oncology, epidemiology, statistical process control, physics, public policy, combat, real-world optimization, Bayesian analyses, and population dynamics. Dr. Thompson believes that, so far from liberating us from the necessity of modeling, the fast computer enables us to engage in realistic models of processes in , for example, economics, which have not been possible earlier because simple stochastic models in the forward temporal direction generally become quite unmanageably complex when one is looking for such things as likelihoods. Thompson shows how simulation may be used to bypass the necessity of obtaining likelihood functions or moment-generating functions as a precursor to parameter estimation. Simulation: A Modeler's Approach is a provocative and practical guide for professionals in applied statistics as well as engineers, scientists, computer scientists, financial analysts, and anyone with an interest in the synergy between data, models, and the digital computer.
Download or read book Statistical Tools for Nonlinear Regression written by Sylvie Huet and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.
Download or read book Methodology in Robust and Nonparametric Statistics written by Jana Jurečková and published by CRC Press. This book was released on 2012-07-20 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from biomedical sciences to the public health disciplines, and, more recently, in genomics, bioinformatics, and financial statistics. These disciplines are presently nourished by data mining and high-level computer-based algorithms, but to work actively with robust and nonparametric procedures, practitioners need to understand their background. Explaining the underpinnings of robust methods and recent theoretical developments, Methodology in Robust and Nonparametric Statistics provides a profound mathematically rigorous explanation of the methodology of robust and nonparametric statistical procedures. Thoroughly up-to-date, this book Presents multivariate robust and nonparametric estimation with special emphasis on affine-equivariant procedures, followed by hypotheses testing and confidence sets Keeps mathematical abstractions at bay while remaining largely theoretical Provides a pool of basic mathematical tools used throughout the book in derivations of main results The methodology presented, with due emphasis on asymptotics and interrelations, will pave the way for further developments on robust statistical procedures in more complex models. Using examples to illustrate the methods, the text highlights applications in the fields of biomedical science, bioinformatics, finance, and engineering. In addition, the authors provide exercises in the text.
Download or read book Stochastic Processes for Insurance and Finance written by Tomasz Rolski and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Processes for Insurance and Finance offers a thorough yet accessible reference for researchers and practitioners of insurance mathematics. Building on recent and rapid developments in applied probability, the authors describe in general terms models based on Markov processes, martingales and various types of point processes. Discussing frequently asked insurance questions, the authors present a coherent overview of the subject and specifically address: The principal concepts from insurance and finance Practical examples with real life data Numerical and algorithmic procedures essential for modern insurance practices Assuming competence in probability calculus, this book will provide a fairly rigorous treatment of insurance risk theory recommended for researchers and students interested in applied probability as well as practitioners of actuarial sciences. Wiley Series in Probability and Statistics
Download or read book Fractional Factorial Plans written by Aloke Dey and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-stop reference to fractional factorials and relatedorthogonal arrays. Presenting one of the most dynamic areas of statistical research,this book offers a systematic, rigorous, and up-to-date treatmentof fractional factorial designs and related combinatorialmathematics. Leading statisticians Aloke Dey and Rahul Mukerjeeconsolidate vast amounts of material from the professionalliterature--expertly weaving fractional replication, orthogonalarrays, and optimality aspects. They develop the basic theory offractional factorials using the calculus of factorial arrangements,thereby providing a unified approach to the study of fractionalfactorial plans. An indispensable guide for statisticians inresearch and industry as well as for graduate students, FractionalFactorial Plans features: * Construction procedures of symmetric and asymmetric orthogonalarrays. * Many up-to-date research results on nonexistence. * A chapter on optimal fractional factorials not based onorthogonal arrays. * Trend-free plans, minimum aberration plans, and search andsupersaturated designs. * Numerous examples and extensive references.
Download or read book Design and Analysis of Experiments Introduction to Experimental Design written by Klaus Hinkelmann and published by John Wiley & Sons. This book was released on 1994-03-22 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and analysis of experiments/Hinkelmann.-v.1.
Download or read book Introduction to Linear Regression Analysis written by Douglas C. Montgomery and published by Wiley-Interscience. This book was released on 2001-04-16 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and thoroughly up-to-date look at regression analysis-still the most widely used technique in statistics today As basic to statistics as the Pythagorean theorem is to geometry, regression analysis is a statistical technique for investigating and modeling the relationship between variables. With far-reaching applications in almost every field, regression analysis is used in engineering, the physical and chemical sciences, economics, management, life and biological sciences, and the social sciences. Clearly balancing theory with applications, Introduction to Linear Regression Analysis describes conventional uses of the technique, as well as less common ones, placing linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. Succeeding chapters include detailed coverage of: ? Indicator variables, making the connection between regression and analysis-of-variance modelss ? Variable selection and model-building techniques ? The multicollinearity problem, including its sources, harmful effects, diagnostics, and remedial measures ? Robust regression techniques, including M-estimators, Least Median of Squares, and S-estimation ? Generalized linear models The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation. Topics not usually found in a linear regression textbook, such as nonlinear regression and generalized linear models, yet critical to engineering students and professionals, have also been included. The new critical role of the computer in regression analysis is reflected in the book's expanded discussion of regression diagnostics, where major analytical procedures now available in contemporary software packages, such as SAS, Minitab, and S-Plus, are detailed. The Appendix now includes ample background material on the theory of linear models underlying regression analysis. Data sets from the book, extensive problem solutions, and software hints are available on the ftp site. For other Wiley books by Doug Montgomery, visit our website at www.wiley.com/college/montgomery.
Download or read book A Weak Convergence Approach to the Theory of Large Deviations written by Paul Dupuis and published by John Wiley & Sons. This book was released on 1997-02-27 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applies the well-developed tools of the theory of weak convergenceof probability measures to large deviation analysis--a consistentnew approach The theory of large deviations, one of the most dynamic topics inprobability today, studies rare events in stochastic systems. Thenonlinear nature of the theory contributes both to its richness anddifficulty. This innovative text demonstrates how to employ thewell-established linear techniques of weak convergence theory toprove large deviation results. Beginning with a step-by-stepdevelopment of the approach, the book skillfully guides readersthrough models of increasing complexity covering a wide variety ofrandom variable-level and process-level problems. Representationformulas for large deviation-type expectations are a key tool andare developed systematically for discrete-time problems. Accessible to anyone who has a knowledge of measure theory andmeasure-theoretic probability, A Weak Convergence Approach to theTheory of Large Deviations is important reading for both studentsand researchers.
Download or read book Dental Anthropology written by Kurt W. Alt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shelley Saunders This book offers a welcome diversity of topics covering the broader subjects of teeth and the study of teeth by anthropologists. There is an impressive array of coverage here including the history of anthropological study of the teeth, morphology and structure, pathology and epidemiology, the relationship between nutrition, human behavior and the dentition, age and sex estimation from teeth, and geographic and genetic variation. Most chapter authors have provided thorough reviews of their subjects along with examples of recent analytical work and recommendations for future research. North American researchers should particularly appreciate the access to an extensive European literature cited in the individual chapter bibliographies. Physical anthropologists with even a passing interest in dental research should greet the publication of this book with pleasure since it adds to a growing list of books on how the study of teeth can tell us so much about past human populations. In addition to the archaeological applications, there is the forensic objective of dental anthropology which the editors refer to in their introduction which is dealt with in this volume. The chapters dealing with methods of sex determination, age estimation of juveniles and age estimation of adults using the teeth are exhaustive and exacting and of critical importance to both "osteoarchaeologists" and forensic anthropologists. Authors Liversidge, Herdeg and Rosing provide very clear guidelines for the use of dental formation standards in juvenile age estimation, recommendations that are so obviously necessary at this time.
