Describes techniques used in computational statistics and considers some of the areas of application, such as density estimation and model building. This book explains numerical techniques for transformations, for function approximation, and for optimization. It is suitable for various courses in modern statistics.
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This book describes techniques used in computational statistics and considers some of the areas of applications, such as density estimation and model building, in which computationally intensive methods are useful. In computational statistics, computation is viewed as an instrument of discovery; the role of the computer is not just to store data, perform computations, and produce graphs and tables, but additionally to suggest to the scientist alternative models and theories. Another characteristic of computational statistics is the computational intensity of the methods; even for datasets of medium size, high performance computers are required to perform the computations. Graphical displays and visualization methods are usually integral features of computational statistics.
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Da: HPB-Red, Dallas, TX, U.S.A.
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