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Book
On round-off errors in linear programming
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Year: 1970 Volume: 37 Publisher: Berlin : Springer,

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Book
On round-off errors in linear programming.
Author:
Year: 1970 Volume: 37 Publisher: Berlin,Heidelberg,New York : Springer,

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Quantization noise : roundoff error in digital computation, signal processing, control, and communications
Authors: --- --- ---
ISBN: 9780521886710 9780511754661 9780511409905 0511409907 0521886716 0511408005 9780511408007 9780511408793 051140879X 1107186870 9781107186873 9786611717070 6611717072 0511409362 9780511409363 0511407262 9780511407260 0511754663 128171707X Year: 2008 Publisher: Cambridge : Cambridge University Press,

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If you are working in digital signal processing, control or numerical analysis, you will find this authoritative analysis of quantization noise (roundoff error) invaluable. Do you know where the theory of quantization noise comes from, and under what circumstances it is true? Get answers to these and other important practical questions from expert authors, including the founder of the field and formulator of the theory of quantization noise, Bernard Widrow. The authors describe and analyze uniform quantization, floating-point quantization, and their applications in detail. Key features include: • Analysis of floating point round off • Dither techniques and implementation issues analyzed • Offers heuristic explanations along with rigorous proofs, making it easy to understand 'why' before the mathematical proof is given.

Applied smoothing techniques for data analysis : the kernel approach with S-Plus illustrations
Authors: --- ---
ISBN: 128037523X 9786610375233 0585484104 9780585484105 9781280375231 0198523963 9780198523963 6610375232 Year: 1997 Publisher: [Place of publication not identified] Clarendon Press

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The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored.; S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus.

Applied smoothing techniques for data analysis : the kernel approach with S-Plus illustrations
Authors: ---
ISBN: 0198523963 Year: 1997 Volume: 18 Publisher: Oxford Clarendon

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Here is a clear exposition of nonparametric smoothing methods for statisticians. The focus is applied rather than theoretical, with a large number of illustrations from different disciplines.


Book
Error propagation for difference methods
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Year: 1963 Publisher: New York : Wiley,

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Kernel smoothing in MATLAB : theory and practice of kernel smoothing
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ISBN: 1283635968 9814405493 9789814405492 9814405485 9789814405485 661394842X 9786613948427 9781283635967 Year: 2012 Publisher: Singapore ; Hackensack, NJ : World Scientific,

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Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book provides a concise and comprehensive overview of statistical theory and in addition, emphasis is given to the implementation of presented methods in Matlab. All created programs are included in a special toolbox which is an integral part of the book. This toolbox contains many Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard funct

Kernel smoothing
Authors: ---
ISBN: 0412552701 9780412552700 Year: 1995 Volume: 60 Publisher: London Chapman and Hall


Book
Smoothing splines : methods and applications.
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ISBN: 9781420077551 Year: 2011 Publisher: Boca Raton CRC Press,


Book
Smoothing of multivariate data : density estimation and visualization.
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ISBN: 9780470290880 Year: 2009 Publisher: Hoboken Wiley

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