Nonparametric Estimation of Probability Densities and Regression Curves: 20 (Mathematics and its Applications, 20) - Softcover
Synopsis
'Et moi, ... , si. j'avail su comment en revenir. One service mathematics has rendered !be human race. It has put common sense back jc n'y scrais point a1U: where it belongs, on the topmost sbelf next Jules Verne to \be dusty canister labelled 'discarded non- TIle series is divergent; therefore we may be sense'. able to do something with it Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic bas rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
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Review
`... this book is a useful and significant addition on the lively topic of nonparametric density and regression curve estimation.'
Royal Statistical Society, 154, 1991
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Nonparametric Estimation of Probability Densities and Regression Curves (eng)
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Nonparametric Estimation of Probability Densities and Regression Curves (Mathematics and its Applications)
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Nonparametric Estimation of Probability Densities and Regression Curves
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ISBN 10: 9401076677
ISBN 13: 9789401076678
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Et moi, . , si. j'avail su comment en revenir. One service mathematics has rendered !be human race. It has put common sense back jc n'y scrais point a1U: where it belongs, on the topmost sbelf next Jules Verne to be dusty canister labelled 'discarded non- TIle series is divergent; therefore we may be sense'. able to do something with it Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics . .'; 'One service logic bas rendered com puter science . .'; 'One service category theory has rendered mathematics . .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series. 228 pp. Englisch. Seller Inventory # 9789401076678
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Nonparametric Estimation of Probability Densities and Regression Curves
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Nonparametric Estimation of Probability Densities and Regression Curves
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Nonparametric Estimation of Probability Densities and Regression Curves
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Nonparametric Estimation of Probability Densities and Regression Curves
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 1. Asymptotic Properties of Certain Measures of Deviation for Kernel-Type Non Parametric Estimators of Probability Densities.- 1. Integrated Mean Square Error of Nonparametric Kernel-Type Probability Density Estimators.- 2. The Mean Square Error of Nonparam. Seller Inventory # 5834254
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Nonparametric Estimation of Probability Densities and Regression Curves
Published by
Springer, Springer Feb 2012, 2012
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ISBN 13: 9789401076678
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -1. Asymptotic Properties of Certain Measures of Deviation for Kernel-Type Non Parametric Estimators of Probability Densities.- 1. Integrated Mean Square Error of Nonparametric Kernel-Type Probability Density Estimators.- 2. The Mean Square Error of Nonparametric Kernel-Type Density Estimators.- 2. Strongly Consistent in Functional Metrics Estimators of Probability Density.- 1. Strong Consistency of Kernel-Type Density Estimators in the Norm of the Space C.- 2. Convergence in the L2 Norm of Kernel-Type Density Estimators.- 3. Convergence in Variation of Kernel-Type Density Estimators and its Application to a Nonparametric Estimator of Bayesian Risk in a Classification Problem.- 3. Limiting Distributions of Deviations of Kernel-Type Density Estimators.- 1. Limiting Distribution of Maximal Deviation of Kernel-Type Estimators.- 2. Limiting Distribution of Quadratic Deviation of Two Nonparametric Kernel-Type Density Estimators.- 3. The Asymptotic Power of the Un1n2-Test in the Case of' singular' Close Alternatives.- 4. Testing for Symmetry of a Distribution.- 5. Independence of Tests Based on Kernel-Type Density Estimators.- 4. Nonparametric Estimation of the Regression Curve and Components of a Convolution.- 1. Some Asymptotic Properties of Nonparametric Estimators of Regression Curves.- 2. Strong Consistency of Regression Curve Estimators in the Norm of the Space C(a, b).- 3. Limiting Distribution of the Maximal Deviation of Estimators of Regression Curves.- 4. Limiting Distribution of Quadratic Deviation of Estimators of Regression Curves.- 5. Nonparametric Estimators of Components of a Convolution (S.N. Bernstein's Problem).- 5. Projection Type Nonparametric Estimation of Probability Density.- 1. Consistency of Projection-Type Probability Density Estimator in theNorms of Spaces C and L2.- 2. Limiting Distribution of the Squared Norm of a Projection-Type Density Estimator.- Addendum Limiting Distribution of Quadratic Deviation for a Wide Class of Probability Density Estimators.- 1. Limiting Distribution of Un.- 2. Kernel Density Estimators / Rosenblatt-Parzen Estimators.- 3. Projection Estimators of Probability Density / Chentsov Estimators.- 4. Histogram.- 5. Deviation of Kernel Estimators in the Sence of the Hellinger Distance.- References.- Author Index.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch. Seller Inventory # 9789401076678