Spline Models for Observational Data: Series Number 59 (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 59) - Image 1

£45.00

Society for Industrial and Applied Mathematics (SIAM) Spline Models for Observational Data: Series Number 59 (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 59)

Name: Spline Models for Observational Data: Series Number 59 (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 59)
Brand: Society for Industrial and Applied Mathematics (SIAM)
Price: 47.47 GBP
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This book serves well as an introduction into the more theoretical aspects of the use of spline models. It develops a theory and practice for the estimation of functions from noisy data on functionals. The simplest example is the estimation of a smooth curve, given noisy observations on a finite number of its values. Convergence properties, data based smoothing parameter selection, confidence intervals, and numerical methods are established which are appropriate to a number of problems within this framework. Methods for including side conditions and other prior information in solving ill posed inverse problems are provided. Data which involves samples of random variables with Gaussian, Poisson, binomial, and other distributions are treated in a unified optimization context. Experimental design questions, i.e., which functionals should be observed, are studied in a general context. Extensions to distributed parameter system identification problems are made by considering implicitly defined functionals.

Product Specifications

Brand: Society for Industrial and Applied Mathematics (SIAM)
Format: paperback
ASIN: 0898712440
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Probability & Statistics
Domain: Amazon UK
Release Date: 01 September 1990
Listed Since: 26 January 2007

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Society for Industrial and Applied Mathematics (SIAM) Spline Models for Observational Data: Series Number 59 (CBMS-NSF Regional Conference Series in Applied Mathematics, Series Number 59)

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