Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples.
This book considers various extensions of the topics treated in the first volume of this series, in relation to the class of models and the type of criterion for optimality. The regressors are supposed to belong to a generic finite dimensional Haar linear space, which substitutes for the classical polynomial case. The estimation pertains to a general linear form of the coefficients of the model, extending the interpolation and extrapolation framework; the errors in the model may be correlated, and the model may be heteroscedastic. Non-linear models, as well as multivariate ones, are briefly discussed. The book focuses to a large extent on criteria for optimality, and an entire chapter presents algorithms leading to optimal designs in multivariate models. Elfving’s theory and the theorem of equivalence are presented extensively. The volume presents an account of the theory of the approximation of real valued functions, which makes it self-consistent.
This volume is the English version of the second edition of the bilingual textbook by Rasch, Verdooren and Gowers (1999). A parallel version in German is available from the same publisher. This book is intended for students and experimental scientists in all disciplines and presumes only elementary statistical knowledge. This prerequisite knowledge is summarised briefly in appendix B. Knowledge of differential and integral calculus is not necessary for the understanding of the text. Matrix notation is explained in Appendix C. As well as the correction of errors, the present edition differs from the first by the introduction of some new sections, such as that on testing the equality of two proportions (Section 3.4.4), and the inclusion of sequential tests. All new material is accompanied by descriptions of the relevant SPSS and CADEMO procedures.
The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation. This international conference was devoted to statistical techniques in stochastic simulation, data collection, analysis of scientific experiments, and studies representing broad areas of interest. The previous workshops took place in St. Petersburg, Russia in 1994, 1996, 1998, 2001, 2005, and 2009. The Seventh Workshop took place in the Rimini Campus of the University of Bologna, which is in Rimini’s historical center.
This volume features original contributions and invited review articles on mathematical statistics, statistical simulation and experimental design. The selected peer-reviewed contributions originate from the 8th International Workshop on Simulation held in Vienna in 2015. The book is intended for mathematical statisticians, Ph.D. students and statisticians working in medicine, engineering, pharmacy, psychology, agriculture and other related fields. The International Workshops on Simulation are devoted to statistical techniques in stochastic simulation, data collection, design of scientific experiments and studies representing broad areas of interest. The first 6 workshops took place in St. Petersburg, Russia, in 1994 – 2009 and the 7th workshop was held in Rimini, Italy, in 2013.
Apple, Audi, Braun oder Samsung machen es vor: Gutes Design ist heute eine kritische Voraussetzung für erfolgreiche Produkte. Dieser Klassiker beschreibt die fundamentalen Prinzipien, um Dinge des täglichen Gebrauchs umzuwandeln in unterhaltsame und zufriedenstellende Produkte. Don Norman fordert ein Zusammenspiel von Mensch und Technologie mit dem Ziel, dass Designer und Produktentwickler die Bedürfnisse, Fähigkeiten und Handlungsweisen der Nutzer in den Vordergrund stellen und Designs an diesen angepasst werden. The Design of Everyday Things ist eine informative und spannende Einführung für Designer, Marketer, Produktentwickler und für alle an gutem Design interessierten Menschen. Zum Autor Don Norman ist emeritierter Professor für Kognitionswissenschaften. Er lehrte an der University of California in San Diego und der Northwest University in Illinois. Mitte der Neunzigerjahre leitete Don Norman die Advanced Technology Group bei Apple. Dort prägte er den Begriff der User Experience, um über die reine Benutzbarkeit hinaus eine ganzheitliche Erfahrung der Anwender im Umgang mit Technik in den Vordergrund zu stellen. Norman ist Mitbegründer der Beratungsfirma Nielsen Norman Group und hat unter anderem Autohersteller von BMW bis Toyota beraten. „Keiner kommt an Don Norman vorbei, wenn es um Fragen zu einem Design geht, das sich am Menschen orientiert.“ Brand Eins 7/2013 „Design ist einer der wichtigsten Wettbewerbsvorteile. Dieses Buch macht Spaß zu lesen und ist von größter Bedeutung.” Tom Peters, Co-Autor von „Auf der Suche nach Spitzenleistungen“
The most comprehensive and applied discussion of stated choice experiment constructions available The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. Many aspects of the design of a generic stated choice experiment are independent of its area of application, and until now there has been no single book describing these constructions. This book begins with a brief description of the various areas where stated choice experiments are applicable, including marketing and health economics, transportation, environmental resource economics, and public welfare analysis. The authors focus on recent research results on the construction of optimal and near-optimal choice experiments and conclude with guidelines and insight on how to properly implement these results. Features of the book include: Construction of generic stated choice experiments for the estimation of main effects only, as well as experiments for the estimation of main effects plus two-factor interactions Constructions for choice sets of any size and for attributes with any number of levels A discussion of designs that contain a none option or a common base option Practical techniques for the implementation of the constructions Class-tested material that presents theoretical discussion of optimal design Complete and extensive references to the mathematical and statistical literature for the constructions Exercise sets in most chapters, which reinforce the understanding of the presented material The Construction of Optimal Stated Choice Experiments serves as an invaluable reference guide for applied statisticians and practitioners in the areas of marketing, health economics, transport, and environmental evaluation. It is also ideal as a supplemental text for courses in the design of experiments, decision support systems, and choice models. A companion web site is available for readers to access web-based software that can be used to implement the constructions described in the book.
Grundlagen der Entwicklung und Konzeption klassischer Spiele von einem der weltweit führenden Game Designer Mehr als 100 Regeln und zentrale Fragen zur Inspiration für den kreativen Prozess Zahlreiche wertvolle Denkanstöße für die Konzeption eines erfolgreichen Spiels Jeder kann die Grundlagen des Game Designs meistern – dazu bedarf es keines technischen Fachwissens. Dabei zeigt sich, dass die gleichen psychologischen Grundprinzipien, die für Brett-, Karten- und Sportspiele funktionieren, ebenso der Schlüssel für die Entwicklung qualitativ hochwertiger Videospiele sind. Mit diesem Buch lernen Sie, wie Sie im Prozess der Spielekonzeption und -entwicklung vorgehen, um bessere Games zu kreieren. Jesse Schell zeigt, wie Sie Ihr Game durch eine strukturierte methodische Vorgehensweise Schritt für Schritt deutlich verbessern. Mehr als 100 gezielte Fragestellungen eröffnen Ihnen dabei neue Perspektiven auf Ihr Game, so dass Sie die Features finden, die es erfolgreich machen. Hierzu gehören z.B. Fragen wie: Welche Herausforderungen stellt mein Spiel an die Spieler? Fördert es den Wettbewerb unter den Spielern? Werden sie dazu motiviert, gewinnen zu wollen? So werden über hundert entscheidende Charakteristika für ein gut konzipiertes Spiel untersucht. Mit diesem Buch wissen Sie, worauf es bei einem guten Game ankommt und was Sie alles bedenken sollten, damit Ihr Game die Erwartungen Ihrer Spieler erfüllt und gerne gespielt wird. Zugleich liefert es Ihnen jede Menge Inspiration – halten Sie beim Lesen Zettel und Stift bereit, um Ihre neuen Ideen sofort festhalten zu können
The last twenty years have witnessed a significant growth of interest in optimal factorial designs, under possible model uncertainty, via the minimum aberration and related criteria. This book gives, for the first time in book form, a comprehensive and up-to-date account of this modern theory. Many major classes of designs are covered in the book. While maintaining a high level of mathematical rigor, it also provides extensive design tables for research and practical purposes. Apart from being useful to researchers and practitioners, the book can form the core of a graduate level course in experimental design.
A state-of-the-art presentation of optimum spatio-temporalsampling design - bridging classic ideas with modern statisticalmodeling concepts and the latest computational methods. Spatio-temporal Design presents a comprehensivestate-of-the-art presentation combining both classical and moderntreatments of network design and planning for spatial andspatio-temporal data acquisition. A common problem set isinterwoven throughout the chapters, providing various perspectivesto illustrate a complete insight to the problem at hand. Motivated by the high demand for statistical analysis of datathat takes spatial and spatio-temporal information into account,this book incorporates ideas from the areas of time series, spatialstatistics and stochastic processes, and combines them to discussoptimum spatio-temporal sampling design. Spatio-temporal Design: Advances in Efficient DataAcquisition: Provides an up-to-date account of how to collect space-timedata for monitoring, with a focus on statistical aspects and thelatest computational methods Discusses basic methods and distinguishes between design andmodel-based approaches to collecting space-time data. Features model-based frequentist design for univariate andmultivariate geostatistics, and second-phase spatial sampling. Integrates common data examples and case studies throughout thebook in order to demonstrate the different approaches and theirintegration. Includes real data sets, data generating mechanisms andsimulation scenarios. Accompanied by a supporting website featuring R code. Spatio-temporal Design presents an excellent book forgraduate level students as well as a valuable reference forresearchers and practitioners in the fields of applied mathematics,engineering, and the environmental and health sciences.

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