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sciences and statistics, Statistical Computing Environments for Social Research describes seven statistical computing environments--APL2STAT, GAUSS;
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sciences and statistics, Statistical Computing Environments for Social Research describes seven statistical computing environments--APL2STAT, GAUSS;
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of statistical computing. ---Mathematics of Computation . The text is highly readable and well illustrated with examples. The reader who intends to take;
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development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements;
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A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has;
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Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve;
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-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data;
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-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data;
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At last-a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature;
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, and application of algorithms for solving statistical problems. After a brief introduction to parallel computing, the book explores the;
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statistical computing are two areas within statistics that may be broadly described as computational, graphical, and numerical approaches to solving;
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scatter plots; to simulate probability models in order to illustrate probability and statistical theory. Explains how to tackle computing;
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Statistical Computing in Nuclear Imaging introduces aspects of Bayesian computing in nuclear imaging. The book provides an introduction to;
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Statistical Computing in Nuclear Imaging introduces aspects of Bayesian computing in nuclear imaging. The book provides an introduction to;
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The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25;
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between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18;
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between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18;
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Offers the useful topics of statistical tools and methods delivered in a student friendly, step-by-step format. This title illustrates;
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This book is a collection of lecture notes from the Symposium on Quantum Computing, Thermodynamics, and Statistical Physics, held at Kinki;
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This book is a collection of contributions to the Symposium on Interface between Quantum Information and Statistical Physics held at Kinki;
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Distribution-free statistical methods enable users to make statistical inferences with minimum assumptions about the population in question;
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Distribution-free statistical methods enable users to make statistical inferences with minimum assumptions about the population;
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An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied;
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Over recent years, developments in statistical computing have freed statisticians from the burden of calculation and have made possible new;
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, internet security, pattern recognition, predictive analytics applications in healthcare, sensor networks and social sensing and statistical;
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information and statistical computing, learning algorithms, system security, virtual reality, cloud computing, service oriented architecture;
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Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams;
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