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This book is intended for students of mathematical statistics who are interested in the early history of their subject. It gives detailed algebraic descriptions of the fitting of linear relationships by the method of least squares (L ) and the related least absolute 2 deviations (L ) and minimax absolute deviations (Loo) procedures. These traditional line J fitting procedures are, of course, also addressed in conventional statistical textbooks, but the discussion of their historical background is usually extremely slight, if not entirely absent. The present book complements the analysis of these procedures given in S.M. Stigler'S excellent work The History of Statistics: The Quantification of Uncertainty before 1900. However, the present book gives a more detailed account of the algebraic structure underlying these traditional fitting procedures. It is anticipated that readers of the present book will obtain a clear understanding of the historical background to these and other commonly used statistical procedures. Further, a careful consideration of the wide variety of distinct approaches to a particular topic, such as the method of least squares, will give the reader valuable insights into the essential nature of the selected topic.
Mathematical statistics --- History. --- 519.233 --- Parametric methods --- 519.233 Parametric methods --- History --- Applied mathematics. --- Engineering mathematics. --- Applications of Mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Mathematical statistics - History.
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This is the second of a two-volume work intended to function as a textbook well as a reference work for economic for graduate students in economics, as scholars who are either working in theory, or who have a strong interest in economic theory. While it is not necessary that a student read the first volume before tackling this one, it may make things easier to have done so. In any case, the student undertaking a serious study of this volume should be familiar with the theories of continuity, convergence and convexity in Euclidean space, and have had a fairly sophisticated semester's work in Linear Algebra. While I have set forth my reasons for writing these volumes in the preface to Volume 1 of this work, it is perhaps in order to repeat that explanation here. I have undertaken this project for three principal reasons. In the first place, I have collected a number of results which are frequently useful in economics, but for which exact statements and proofs are rather difficult to find; for example, a number of results on convex sets and their separation by hyperplanes, some results on correspondences, and some results concerning support functions and their duals. Secondly, while the mathematical top ics taken up in these two volumes are generally taught somewhere in the mathematics curriculum, they are never (insofar as I am aware) done in a two-course sequence as they are arranged here.
Mathematics --- Economics, Mathematical --- Economics, Mathematical. --- Economic theory. --- Applied mathematics. --- Engineering mathematics. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Applications of Mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- Economic theory --- Political economy --- Social sciences --- Economic man --- Economics --- Mathematical economics --- Econometrics --- Methodology --- Mathématiques économiques --- Économie politique --- Modèles mathématiques --- Mathématiques économiques --- Économie politique --- Modèles mathématiques
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This volume presents an overview of Bayesian methods for inference in the wavelet domain. The papers in this volume are divided into six parts: The first two papers introduce basic concepts. Chapters in Part II explore different approaches to prior modeling, using independent priors. Papers in the Part III discuss decision theoretic aspects of such prior models. In Part IV, some aspects of prior modeling using priors that account for dependence are explored. Part V considers the use of 2-dimensional wavelet decomposition in spatial modeling. Chapters in Part VI discuss the use of empirical Bayes estimation in wavelet based models. Part VII concludes the volume with a discussion of case studies using wavelet based Bayesian approaches. The cooperation of all contributors in the timely preparation of their manuscripts is greatly recognized. We decided early on that it was impor tant to referee and critically evaluate the papers which were submitted for inclusion in this volume. For this substantial task, we relied on the service of numerous referees to whom we are most indebted. We are also grateful to John Kimmel and the Springer-Verlag referees for considering our proposal in a very timely manner. Our special thanks go to our spouses, Gautami and Draga, for their support.
Bayesian statistical decision theory --- Wavelets (Mathematics) --- Statistique bayésienne --- Ondelettes --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Bayesian statistical decision theory. --- Statistique bayésienne --- Applied mathematics. --- Engineering mathematics. --- Applications of Mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- Wavelet analysis --- Harmonic analysis --- Bayes' solution --- Bayesian analysis --- Statistical decision
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Over the past decade there has been an increasing demand for suitable material in the area of mathematical modelling as applied to science and engineering. There has been a constant movement in the emphasis from developing proficiency in purely mathematical techniques to an approach which caters for industrial and scientific applications in emerging new technologies. In this textbook we have attempted to present the important fundamental concepts of mathematical modelling and to demonstrate their use in solving certain scientific and engineering problems. This text, which serves as a general introduction to the area of mathematical modelling, is aimed at advanced undergraduate students in mathematics or closely related disciplines, e.g., students who have some prerequisite knowledge such as one-variable calculus, linear algebra and ordinary differential equations. Some prior knowledge of computer programming would be useful but is not considered essential. The text also contains some more challenging material which could prove attractive to graduate students in engineering or science who are involved in mathematical modelling. In preparing the text we have tried to use our experience of teaching mathematical modelling to undergraduate students in a wide range of areas including mathematics and computer science and disciplines in engineering and science. An important aspect of the text is the use made of scientific computer software packages such as MAPLE for symbolic algebraic manipulations and MA TLAB for numerical simulation.
Mathematical logic --- Operational research. Game theory --- Mathematical models. --- Applied mathematics. --- Engineering mathematics. --- Vibration. --- Dynamical systems. --- Dynamics. --- Mathematical Modeling and Industrial Mathematics. --- Applications of Mathematics. --- Vibration, Dynamical Systems, Control. --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Cycles --- Sound --- Engineering --- Engineering analysis --- Mathematical analysis --- Models, Mathematical --- Simulation methods --- Mathématiques --- Modèles mathématiques
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Joseph-Louis Lagrange (1736-1813), one of the greatest mathematicians of the 18th century, made important contributions to the theory of numbers and to analytical and celestial mechanics. His most important work is Mecanique Analytique (1788), the textbook on which all subsequent work in this field is based. A contempo rary reader is surprised to find no diagrams or figures of any kind in this book on mechanics. This reflects one extreme approach to graphics, namely considering it unimportant or even detracting as a teaching tool and not using it. Today, of course, this approach is unthinkable. Graphics, especially computer graphics, is commonly used in texts, advertisements, and movies to illustrate concepts, to emphasize points being discussed, and to entertain. Our approach to graphics has been completely reversed since the days of La grange, and it seems that much of this change is due to the use of computers. Computer graphics today is a mature, successful, and growing field. It is used by many people for many purposes and it is enjoyed by even more people. One criterion for the maturity of a field of study is its size. When a certain discipline becomes so big that no one person can keep all of it in their head, we say that that discipline has matured (or has come of age). This is what happened to computer graphics in the last decade or so.
Artificial intelligence. Robotics. Simulation. Graphics --- Computer graphics. --- Mathematical models. --- Computer science. --- Computer simulation. --- Mathematics. --- Engineering & Applied Sciences --- Technology - General --- Computer graphics --- Mathematical models --- Applied mathematics. --- Engineering mathematics. --- Simulation and Modeling. --- Computer Graphics. --- Applications of Mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Image processing --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Simulation methods --- Model-integrated computing --- Mathematics --- Digital techniques --- Models, Mathematical
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517.91 --- 517.95 --- Mathematical physics --- Painleve equations --- Equations, Painlevé --- Functions, Painlevé --- Painlevé functions --- Painlevé transcendents --- Transcendents, Painlevé --- Differential equations, Nonlinear --- Physical mathematics --- Physics --- Ordinary differential equations: general theory --- Partial differential equations --- Mathematics --- Painlevâe equations --- Engineering & Applied Sciences --- Applied Physics --- 517.95 Partial differential equations --- 517.91 Ordinary differential equations: general theory --- Painlevé equations. --- Mathematical physics. --- Painlevé equations --- Applied mathematics. --- Engineering mathematics. --- Theoretical, Mathematical and Computational Physics. --- Applications of Mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- PainleveÌ equations. --- Equations differentielles non lineaires
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Harmonic analysis. Fourier analysis --- Fourier analysis --- Analyse de Fourier --- 517.518.5 --- 517.518.4 --- Analysis, Fourier --- Mathematical analysis --- Theory of the Fourier integral --- Trigonometric series --- Fourier analysis. --- 517.518.4 Trigonometric series --- 517.518.5 Theory of the Fourier integral --- Functional analysis. --- Applied mathematics. --- Engineering mathematics. --- Mathematical analysis. --- Analysis (Mathematics). --- Computational intelligence. --- Chemometrics. --- Functional Analysis. --- Applications of Mathematics. --- Analysis. --- Computational Intelligence. --- Math. Applications in Chemistry. --- Chemistry, Analytic --- Analytical chemistry --- Chemistry --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- 517.1 Mathematical analysis --- Engineering --- Engineering analysis --- Functional calculus --- Calculus of variations --- Functional equations --- Integral equations --- Mathematics --- Measurement --- Statistical methods
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This significantly expanded second edition of Riemann, Topology, and Physics combines a fascinating account of the life and work of Bernhard Riemann with a lucid discussion of current interaction between topology and physics. The author, a distinguished mathematical physicist, takes into account his own research at the Riemann archives of Göttingen University and developments over the last decade that connect Riemann with numerous significant ideas and methods reflected throughout contemporary mathematics and physics. Special attention is paid in part one to results on the Riemann–Hilbert problem and, in part two, to discoveries in field theory and condensed matter such as the quantum Hall effect, quasicrystals, membranes with nontrivial topology, "fake" differential structures on 4-dimensional Euclidean space, new invariants of knots and more. In his relatively short lifetime, this great mathematician made outstanding contributions to nearly all branches of mathematics; today Riemann’s name appears prominently throughout the literature. "The book is highly recommendable—for students and scientific workers—not only for the valuable information in it, but also for its spirit: history and higher mathematics are not dry here; they become alive and motivate further studies."—ZAA "This is a new translation of a book first published in English in 1987... Translated from Russian...it consists of two separate but related works. The first is an account of the life and work of Riemann, the second an account of several different topics in physics which are illuminated by the introduction of topological ideas. The discussion of Riemann is even better in the new edition. The mathematical account is richer and various errors have been corrected... The second half has been revised in a similar fashion... It has also been enriched by a new chapter which starts with von Neumann algebras and the work of Vaughn Jones... The book does three things very well: it reminds us of the range and depth of Riemann’s interests, which are emblematic of what the author values in mathematical physics; describes some of the many successes of Russian mathematicians and physicists; and it provides a lucid account of some modern work in which topology is genuinely applied. Books like this are vital for the health of mathematics and it is to be hoped that more will be written."---Mathematical Reviews.
Topology --- Physics --- Differential geometry. Global analysis --- Mathematicians --- Mathematical physics --- Biography --- Riemann, Bernhard --- Mathematics --- Physical Sciences & Mathematics --- Mathematics - General --- Applied Mathematics --- Engineering & Applied Sciences --- Applied mathematics. --- Engineering mathematics. --- Physics. --- Topology. --- Mathematics. --- History. --- Applications of Mathematics. --- Mathematical Methods in Physics. --- History of Mathematical Sciences. --- Annals --- Auxiliary sciences of history --- Math --- Science --- Analysis situs --- Position analysis --- Rubber-sheet geometry --- Geometry --- Polyhedra --- Set theory --- Algebras, Linear --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematical physics. --- Riemann, Bernhard, --- Physical mathematics --- Riemann, B. --- Riman, Georg Fridrikh Bernkhard, --- Riman, Bernkhard, --- Riemann, Georg Friedrich Bernhard, --- Mathematicians - Germany - Biography
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This book, like many books, was born in frustration. When in the fall of 1994 I set out to teach a second course in computational statistics to d- toral students at the University of Michigan, none of the existing texts seemed exactly right. On the one hand, the many decent, even inspiring, books on elementary computational statistics stress the nuts and bolts of using packaged programs and emphasize model interpretation more than numerical analysis. On the other hand, the many theoretical texts in - merical analysis almost entirely neglect the issues of most importance to statisticians. TheclosestbooktomyidealwastheclassicaltextofKennedy and Gentle [2]. More than a decade and a half after its publication, this book still has many valuable lessons to teach statisticians. However, upon re?ecting on the rapid evolution of computational statistics, I decided that the time was ripe for an update. The book you see before you represents a biased selection of those topics in theoretical numerical analysis most relevant to statistics. By intent this book is not a compendium of tried and trusted algorithms, is not a c- sumer’s guide to existing statistical software, and is not an exposition of computer graphics or exploratory data analysis. My focus on principles of numerical analysis is intended to equip students to craft their own software and to understand the advantages and disadvantages of di?erent numerical methods. Issues of numerical stability, accurate approximation, compu- tional complexity, and mathematical modeling share the limelight and take precedence over philosophical questions of statistical inference.
AA / International- internationaal --- 304.0 --- 303.0 --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Numerical analysis. --- Statistique mathématique --- 519.4 --- Applied Mathematics --- Mathematics. --- Applied mathematics. --- Engineering mathematics. --- Applications of Mathematics. --- Mathematical statistics --- Numerical analysis --- 519.2 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Mathematical analysis --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- Statistical methods --- Mathematical statistics. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Engineering --- Engineering analysis
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The 7th International Workshop in Analysis and its Applications (IWAA) was held at the University of Maine, June 1-6, 1997 and featured approxi mately 60 mathematicians. The principal theme of the workshop shares the title of this volume and the latter is a direct outgrowth of the workshop. IWAA was founded in 1984 by Professor Caslav V. Stanojevic. The first meeting was held in the resort complex Kupuri, Yugoslavia, June 1-10, 1986, with two pilot meetings preceding. The Organization Committee to gether with the Advisory Committee (R. P. Boas, R. R. Goldberg, J. P. Kahne) set forward the format and content of future meetings. A certain number of papers were presented that later appeared individually in such journals as the Proceedings of the AMS, Bulletin of the AMS, Mathematis chen Annalen, and the Journal of Mathematical Analysis and its Applica tions. The second meeting took place June 1-10, 1987, at the same location. At the plenary session of this meeting it was decided that future meetings should have a principal theme. The theme for the third meeting (June 1- 10, 1989, Kupuri) was Karamata's Regular Variation. The principal theme for the fourth meeting (June 1-10, 1990, Kupuri) was Inner Product and Convexity Structures in Analysis, Mathematical Physics, and Economics. The fifth meeting was to have had the theme, Analysis and Foundations, organized in cooperation with Professor A. Blass (June 1-10, 1991, Kupuri).
Control theory. --- Divergent series. --- Asymptotic expansions. --- Asymptotic developments --- Asymptotes --- Convergence --- Difference equations --- Divergent series --- Functions --- Numerical analysis --- Series, Divergent --- Series --- Dynamics --- Machine theory --- Asymptotic expansions --- Control theory --- Applied mathematics. --- Engineering mathematics. --- Signal processing. --- Image processing. --- Speech processing systems. --- Functional analysis. --- Applications of Mathematics. --- Signal, Image and Speech Processing. --- Functional Analysis. --- Functional calculus --- Calculus of variations --- Functional equations --- Integral equations --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics
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