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＜電子ブック＞
Elements of Computational Statistics / by James E. Gentle
(Statistics and Computing. ISSN:21971706)

版	1st ed. 2002.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2002
本文言語	英語
大きさ	XVIII, 420 p : online resource
著者標目	*Gentle, James E author SpringerLink (Online service)
件　名	LCSH:Mathematical statistics -- Data processing  全ての件名で検索 FREE:Statistics and Computing
一般注記	Methods of Computational Statistics -- Preliminaries -- Monte Carlo Methods for Inference -- Randomization and Data Partitioning -- Bootstrap Methods -- Tools for Identification of Structure in Data -- Estimation of Functions -- Graphical Methods in Computational Statistics -- Data Density and Structure -- Estimation of Probability Density Functions Using Parametric Models -- Nonparametric Estimation of Probability Density Functions -- Structure in Data -- Statistical Models of Dependencies 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 HTTP:URL=https://doi.org/10.1007/b97337

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