TY - BOOK ID - 8286442 TI - Computational Statistics PY - 2009 SN - 0387981438 0387981454 9786612827297 1282827294 0387981446 9780387981437 PB - New York, NY : Springer New York : Imprint: Springer, DB - UniCat KW - Mathematical statistics -- Congresses. KW - Mathematical statistics -- Data processing. KW - Mathematical statistics. KW - Probabilities -- Data processing. KW - Mathematical statistics KW - Mathematical Statistics KW - Mathematics KW - Physical Sciences & Mathematics KW - Data processing KW - Statistics KW - Data processing. KW - Mathematics. KW - Computer science KW - Numerical analysis. KW - Data mining. KW - Computer mathematics. KW - Probabilities. KW - Statistics. KW - Probability Theory and Stochastic Processes. KW - Computational Mathematics and Numerical Analysis. KW - Mathematics of Computing. KW - Statistics and Computing/Statistics Programs. KW - Numeric Computing. KW - Data Mining and Knowledge Discovery. KW - Distribution (Probability theory. KW - Computer science. KW - Electronic data processing. KW - Algorithmic knowledge discovery KW - Factual data analysis KW - KDD (Information retrieval) KW - Knowledge discovery in data KW - Knowledge discovery in databases KW - Mining, Data KW - Database searching KW - ADP (Data processing) KW - Automatic data processing KW - EDP (Data processing) KW - IDP (Data processing) KW - Integrated data processing KW - Computers KW - Office practice KW - Statistical inference KW - Statistics, Mathematical KW - Probabilities KW - Sampling (Statistics) KW - Informatics KW - Science KW - Computer mathematics KW - Discrete mathematics KW - Electronic data processing KW - Distribution functions KW - Frequency distribution KW - Characteristic functions KW - Automation KW - Statistical methods KW - Computer science—Mathematics. KW - Statistics . KW - Mathematical analysis KW - Statistical analysis KW - Statistical data KW - Statistical science KW - Econometrics KW - Probability KW - Combinations KW - Chance KW - Least squares KW - Risk KW - Mathematical statistics - Data processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:8286442 AB - Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods. Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods. The book assumes an intermediate background in mathematics, computing, and applied and theoretical statistics. The first part of the book, consisting of a single long chapter, reviews this background material while introducing computationally-intensive exploratory data analysis and computational inference. The six chapters in the second part of the book are on statistical computing. This part describes arithmetic in digital computers and how the nature of digital computations affects algorithms used in statistical methods. Building on the first chapters on numerical computations and algorithm design, the following chapters cover the main areas of statistical numerical analysis, that is, approximation of functions, numerical quadrature, numerical linear algebra, solution of nonlinear equations, optimization, and random number generation. The third and fourth parts of the book cover methods of computational statistics, including Monte Carlo methods, randomization and cross validation, the bootstrap, probability density estimation, and statistical learning. The book includes a large number of exercises with some solutions provided in an appendix. James E. Gentle is University Professor of Computational Statistics at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for the Advancement of Science. He has held several national offices in the ASA and has served as associate editor of journals of the ASA as well as for other journals in statistics and computing. He is author of Random Number Generation and Monte Carlo Methods and Matrix Algebra. ER -