Spline Models for Observational Data

Spline Models for Observational Data PDF Author: Grace Wahba
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 169

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Book Description

Spline Models for Observational Data

Spline Models for Observational Data PDF Author: Grace Wahba
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 169

Get Book Here

Book Description


Spline Models for Observational Data

Spline Models for Observational Data PDF Author: Grace Wahba
Publisher: SIAM
ISBN: 9781611970128
Category : Mathematics
Languages : en
Pages : 181

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Book Description
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. The estimate is a polynomial smoothing spline. By placing this smoothing problem in the setting of reproducing kernel Hilbert spaces, a theory is developed which includes univariate smoothing splines, thin plate splines in d dimensions, splines on the sphere, additive splines, and interaction splines in a single framework. A straightforward generalization allows the theory to encompass the very important area of (Tikhonov) regularization methods for ill-posed inverse problems. Convergence properties, data based smoothing parameter selection, confidence intervals, and numerical methods are established which are appropriate to a wide variety of problems which fall within this framework. Methods for including side conditions and other prior information in solving ill-posed inverse problems are included. 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.

Spline Models for Observational Data

Spline Models for Observational Data PDF Author: Grace Wahba
Publisher: SIAM
ISBN: 0898712440
Category : Mathematics
Languages : en
Pages : 174

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Book Description
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.

Multivariate Splines

Multivariate Splines PDF Author: Charles K. Chui
Publisher: SIAM
ISBN: 0898712262
Category : Mathematics
Languages : en
Pages : 192

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Book Description
Subject of multivariate splines presented from an elementary point of view; includes many open problems.

Smoothing Splines

Smoothing Splines PDF Author: Yuedong Wang
Publisher: CRC Press
ISBN: 1420077562
Category : Computers
Languages : en
Pages : 380

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Book Description
A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent years and has been widely used in many application areas, from medicine to economics. Smoothing Splines: Methods and Applications covers basic smoothing spline models, including polynomial, periodic, spherical, t

Statistical Theory and Computational Aspects of Smoothing

Statistical Theory and Computational Aspects of Smoothing PDF Author: Wolfgang Härdle
Publisher: Springer Science & Business Media
ISBN: 3642484255
Category : Business & Economics
Languages : en
Pages : 265

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Book Description
One of the main applications of statistical smoothing techniques is nonparametric regression. For the last 15 years there has been a strong theoretical interest in the development of such techniques. Related algorithmic concepts have been a main concern in computational statistics. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. But they are also relevant for medical and psychological research. Introduced are new developments in scatterplot smoothing and applications in statistical modelling. The treatment of the topics is on an intermediate level avoiding too much technicalities. Computational and applied aspects are considered throughout. Of particular interest to readers is the discussion of recent local fitting techniques.

Smoothing Spline ANOVA Models

Smoothing Spline ANOVA Models PDF Author: Chong Gu
Publisher: Springer Science & Business Media
ISBN: 1461453690
Category : Mathematics
Languages : en
Pages : 446

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Book Description
Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians. Assisted by the ample computing power in today's servers, desktops, and laptops, smoothing methods have been finding their ways into everyday data analysis by practitioners. While scores of methods have proved successful for univariate smoothing, ones practical in multivariate settings number far less. Smoothing spline ANOVA models are a versatile family of smoothing methods derived through roughness penalties, that are suitable for both univariate and multivariate problems. In this book, the author presents a treatise on penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses as well as with censored lifetime data; (ii) density and conditional density estimation under a variety of sampling schemes; and (iii) hazard rate estimation with censored life time data and covariates. The unifying themes are the general penalized likelihood method and the construction of multivariate models with built-in ANOVA decompositions. Extensive discussions are devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most of the computational and data analytical tools discussed in the book are implemented in R, an open-source platform for statistical computing and graphics. Suites of functions are embodied in the R package gss, and are illustrated throughout the book using simulated and real data examples. This monograph will be useful as a reference work for researchers in theoretical and applied statistics as well as for those in other related disciplines. It can also be used as a text for graduate level courses on the subject. Most of the materials are accessible to a second year graduate student with a good training in calculus and linear algebra and working knowledge in basic statistical inferences such as linear models and maximum likelihood estimates.

Topics in Splines and Applications

Topics in Splines and Applications PDF Author: Young Kinh-Nhue Truong
Publisher: BoD – Books on Demand
ISBN: 1789232503
Category : Computers
Languages : en
Pages : 162

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Book Description
Splines provide a significant tool for the design of computationally economical curves and surfaces for the construction of various objects like automobiles, ship hulls, airplane fuselages and wings, propeller blades, shoe insoles, bottles, etc. It also contributes in the description of geological, physical, statistical, and even medical phenomena. Spline methods have proven to be indispensable in a variety of modern industries, including computer vision, robotics, signal and image processing, visualization, textile, graphic designs, and even media. This book aims to provide a valuable source on splines and their applications. It focuses on collecting and disseminating information in various disciplines including computer-aided geometric design, computer graphics, data visualization, data fitting, power systems, clinical and epidemiologic studies, disease detection, regression curves, social media, and biological studies. The book is useful for researchers, scientists, practitioners, and many others who seek state-of-the-art techniques and applications using splines. It is also useful for undergraduate senior students as well as graduate students in the areas of computer science, engineering, health science, statistics, and mathematics. Each chapter also provides useful information on software developments and their extensions.

Multivariate Model Building and Model Identification

Multivariate Model Building and Model Identification PDF Author: Grace Wahba
Publisher:
ISBN:
Category :
Languages : en
Pages : 4

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Book Description
A very substantial number of results were obtained during this contract in the area of multivariate model building and model identification. A list of publications in which the Air Force Contract is mentioned appears below. We are continuing this work in the follow on contract, AFOSR 90-0103. The research monograph Spline Models for Observational Data by the PI was published by The Society for Industrial and Applied Mathematics in March 1990 as volume 59 in the prestigious CBMS-NSF Regional Conference Series in Applied Mathematics. Although the actual writing of this monograph was not supported by the AFOSR, a number of research results obtained under AFOSR sponsorship are discussed in it. We have acknowledged in the Foreword the research support of the AFOSR. (kr).

Nonparametric Regression and Spline Smoothing, Second Edition

Nonparametric Regression and Spline Smoothing, Second Edition PDF Author: Randall L. Eubank
Publisher: CRC Press
ISBN: 9780824793371
Category : Mathematics
Languages : en
Pages : 368

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Book Description
Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.