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Graphics of large datasets : visualizing a million / par Unwin, Antony. Publication : [S.l.] : Springer, 2006 . 271 p. ; , Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day? This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases or large in numbers of variables or large in both. Data visualization is useful for data cleaning, exploring data, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. It is essential for exploratory data analysis and data mining. Data analysts, statisticians, computer scientists-indeed anyone who has to explore a large dataset of their own-should benefit from reading this book. New approaches to graphics are needed to visualize the information in large datasets and most of the innovations described in this book are developments of standard graphics. There are considerable advantages in extending displays which are well-known and well-tried, both in understanding how best to make use of them in your work and in presenting results to others. It should also make the book readily accessible for readers who already have a little experience of drawing statistical graphics. All ideas are illustrated with displays from analyses of real datasets and the authors emphasize the importance of interpreting displays effectively. Graphics should be drawn to convey information and the book includes many insightful examples. From the reviews: "Anyone interested in modern techniques for visualizing data will be well rewarded by reading this book. There is a wealth of important plotting types and techniques." Paul Murrell for the Journal of Statistical Software, December 2006 "This fascinating book looks at the question of visualizing large datasets from many different perspectives. Different authors are responsible for different chapters and this approach works well in giving the reader alternative viewpoints of the same problem. Interestingly the authors have cleverly chosen a definition of 'large dataset'. Essentially they focus on datasets with the order of a million cases. As the authors point out there are now many examples of much larger datasets but by limiting to ones that can be loaded in their entirety in standard statistical software they end up with a book that has great utility to the practitioner rather than just the theorist. Another very attractive feature of the book is the many colour plates, showing clearly what can now routinely be seen on the computer screen. The interactive nature of data analysis with large datasets is hard to reproduce in a book but the authors make an excellent attempt to do just this." P. Marriott for the Short Book Reviews of the ISI. 24 cm. Date : 2006 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Statistical methods in counterterrorism : game theory, modeling, syndromic surveillance, and biometric authentication.   Publication : [S.l.] : Springer, 2006 . 292 p. ; , All the data was out there to warn us of this impending attack, why didn't we see it?" This was a frequently asked question in the weeks and months after the terrorist attacks on the World Trade Center and the Pentagon on September 11, 2001. In the wake of the attacks, statisticians moved quickly to become part of the national response to the global war on terror. This book is an overview of the emerging research program at the intersection of national security and statistical sciences. A wide range of talented researchers address issues in - Syndromic Surveillance---How do we detect and recognize bioterrorist events? - Modeling and Simulation---How do we better understand and explain complex processes so that decision makers can take the best course of action? - Biometric Authentication---How do we pick the terrorist out of the crowd of faces or better match the passport to the traveler? - Game Theory---How do we understand the rules that terrorists are playing by? This book includes technical treatments of statistical issues that will be of use to quantitative researchers as well as more general examinations of quantitative approaches to counterterrorism that will be accessible to decision makers with stronger policy backgrounds. Dr. Alyson G. Wilson is a statistician and the technical lead for DoD programs in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. Gregory D. Wilson is a rhetorician and ethnographer in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. David H. Olwell is chair of the Department of Systems Engineering at the Naval Postgraduate School in Monterey, California. 24 cm. Date : 2006 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Juridiques, Economiques et de Gestion (1),

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A Probability Path par Resnick, Sidney I. Publication : . XIV, 453 p. 11 illus. Disponibilité :  http://dx.doi.org/10.1007/978-0-8176-8409-9,

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Informal Introduction to Stochastic Processes with Maple par Vrbik, Jan. Publication : . X, 287 p. 54 illus. Disponibilité :  http://dx.doi.org/10.1007/978-1-4614-4057-4,

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Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis par Kjærulff, Uffe B. Publication : . XVIII, 382 p. Disponibilité :  http://dx.doi.org/10.1007/978-1-4614-5104-4,

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Understanding Policy Decisions par Dente, Bruno. Publication : . VIII, 134 p. 11 illus. Disponibilité :  http://dx.doi.org/10.1007/978-3-319-02520-9,

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Applied Conjoint Analysis par Rao, Vithala R. Publication : . XV, 389 p. 56 illus. Disponibilité :  http://dx.doi.org/10.1007/978-3-540-87753-0,

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Performance Analysis of Closed Queueing Networks par Lagershausen, Svenja. Publication : . XXIII, 169 p. 49 illus., 5 illus. in color. Disponibilité :  http://dx.doi.org/10.1007/978-3-642-32214-3,

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