Ditemukan 7 dokumen yang sesuai dengan query
Thompson, James R.
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Topics emphasized include nonparametric density estimation as an exploratory device plus the deeper models to which the exploratory analysis points, multi-dimensional data analysis, and analysis of remote sensing data, cancer progression, chaos theory, epidemiological modeling, and parallel based algorithms. New methods discussed are quick nonparametric density estimation based techniques for resampling and simulation based estimation techniques not requiring closed form solutions ...
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Philadelphia : Society for Industrial and Applied Mathematics, 1990
e20442929
eBooks Universitas Indonesia Library
Keating, Jerome P.
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Pitman's Measure of Closeness (PMC) is simply an idea whose time has come. Certainly there are many different ways to estimate unknown parameters, but which method should you use? Posed as an alternative to the concept of mean-squared-error, PMC is based on the probabilities of the closeness of competing estimators to an unknown parameter. Renewed interest in PMC over the last 20 years has motivated the authors to produce this book, which explores this method ...
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Philadelphia: Society for Industrial and Applied Mathematics, 1993
e20448599
eBooks Universitas Indonesia Library
Speyer, Jason Lee
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Uncertainty and risk are integral to engineering because real systems have inherent ambiguities that arise naturally or due to our inability to model complex physics. The authors discuss probability theory, stochastic processes, estimation, and stochastic control strategies and show how probability can be used to model uncertainty in control and estimation problems. The material is practical and rich in research opportunities.
The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to ...
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Philadelphia: Society for Industrial and Applied Mathematics, 2008
e20450871
eBooks Universitas Indonesia Library
Philadelphia : Society for Industrial and Applied Mathematics, 1992
e20442855
eBooks Universitas Indonesia Library
Efron, Bradley
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The jackknife and the bootstrap are nonparametric methods for assessing the errors in a statistical estimation problem. They provide several advantages over the traditional parametric approach: the methods are easy to describe and they apply to arbitrarily complicated situations; distribution assumptions, such as normality, are never made.
This monograph connects the jackknife, the bootstrap, and many other related ideas such as cross-validation, random subsampling, and balanced repeated replications into a unified exposition. The theoretical development ...
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Philadelphia: Society for Industrial and Applied Mathematics, 1994
e20443362
eBooks Universitas Indonesia Library
Hassibi, Babak
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This monograph presents a unified mathematical framework for a wide range of problems in estimation and control. The authors discuss the two most commonly used methodologies: the stochastic H2 approach and the deterministic (worst-case) H� approach. Despite the fundamental differences in the philosophies of these two approaches, the authors have discovered that, if indefinite metric spaces are considered, they can be treated in the same way and are essentially the same ...
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Philadelphia : Society for Industrial and Applied Mathematics, 1999
e20442846
eBooks Universitas Indonesia Library
O`Gorman, Thomas W.
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Adaptive statistical tests, developed over the last 30 years, are often more powerful than traditional tests of significance, but have not been widely used. To date, discussions of adaptive statistical methods have been scattered across the literature and generally do not include the computer programs necessary to make these adaptive methods a practical alternative to traditional statistical methods. Until recently, there has also not been a general approach to tests of significance and confidence intervals ...
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Philadelphia : Society for Industrial and Applied Mathematics, 2004
e20443005
eBooks Universitas Indonesia Library
