Smoothing Splines PDF Download
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Author | : Chong Gu |
Publisher | : Springer Science & Business Media |
Total Pages | : 446 |
Release | : 2013-01-26 |
Genre | : Mathematics |
ISBN | : 1461453690 |
Download Smoothing Spline ANOVA Models Book in PDF, ePub and Kindle
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.
Author | : Yuedong Wang |
Publisher | : CRC Press |
Total Pages | : 380 |
Release | : 2011-06-22 |
Genre | : Computers |
ISBN | : 1420077562 |
Download Smoothing Splines Book in PDF, ePub and Kindle
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
Author | : Paul H.C. Eilers |
Publisher | : Cambridge University Press |
Total Pages | : 213 |
Release | : 2021-03-18 |
Genre | : Computers |
ISBN | : 1108482953 |
Download Practical Smoothing Book in PDF, ePub and Kindle
This user guide presents a popular smoothing tool with practical applications in machine learning, engineering, and statistics.
Author | : Randall L. Eubank |
Publisher | : CRC Press |
Total Pages | : 368 |
Release | : 1999-02-09 |
Genre | : Mathematics |
ISBN | : 9780824793371 |
Download Nonparametric Regression and Spline Smoothing, Second Edition Book in PDF, ePub and Kindle
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.
Author | : Gary D. Knott |
Publisher | : Springer Science & Business Media |
Total Pages | : 247 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 1461213207 |
Download Interpolating Cubic Splines Book in PDF, ePub and Kindle
A spline is a thin flexible strip composed of a material such as bamboo or steel that can be bent to pass through or near given points in the plane, or in 3-space in a smooth manner. Mechanical engineers and drafting specialists find such (physical) splines useful in designing and in drawing plans for a wide variety of objects, such as for hulls of boats or for the bodies of automobiles where smooth curves need to be specified. These days, physi cal splines are largely replaced by computer software that can compute the desired curves (with appropriate encouragment). The same mathematical ideas used for computing "spline" curves can be extended to allow us to compute "spline" surfaces. The application ofthese mathematical ideas is rather widespread. Spline functions are central to computer graphics disciplines. Spline curves and surfaces are used in computer graphics renderings for both real and imagi nary objects. Computer-aided-design (CAD) systems depend on algorithms for computing spline functions, and splines are used in numerical analysis and statistics. Thus the construction of movies and computer games trav els side-by-side with the art of automobile design, sail construction, and architecture; and statisticians and applied mathematicians use splines as everyday computational tools, often divorced from graphic images.
Author | : Chong Gu |
Publisher | : Springer Science & Business Media |
Total Pages | : 301 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 1475736835 |
Download Smoothing Spline ANOVA Models Book in PDF, ePub and Kindle
Smoothing methods are an active area of research. In this book, the author presents a comprehensive treatment of penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses as well as with censored life time 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. 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 clone of the popular S/S- PLUS language.
Author | : Chong Gu |
Publisher | : Springer Science & Business Media |
Total Pages | : 312 |
Release | : 2002-01-08 |
Genre | : Mathematics |
ISBN | : 9780387953533 |
Download Smoothing Spline ANOVA Models Book in PDF, ePub and Kindle
Smoothing methods are an active area of research. In this book, the author presents a comprehensive treatment of penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses as well as with censored life time 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. 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 clone of the popular S/S- PLUS language.
Author | : Wolfgang Härdle |
Publisher | : Springer Science & Business Media |
Total Pages | : 265 |
Release | : 2013-03-08 |
Genre | : Business & Economics |
ISBN | : 3642484255 |
Download Statistical Theory and Computational Aspects of Smoothing Book in PDF, ePub and Kindle
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.
Author | : Andrej Dobnikar |
Publisher | : Springer Science & Business Media |
Total Pages | : 190 |
Release | : 1999-07-15 |
Genre | : Computers |
ISBN | : 9783211833643 |
Download Artificial Neural Nets and Genetic Algorithms Book in PDF, ePub and Kindle
From the contents: Neural networks – theory and applications: NNs (= neural networks) classifier on continuous data domains– quantum associative memory – a new class of neuron-like discrete filters to image processing – modular NNs for improving generalisation properties – presynaptic inhibition modelling for image processing application – NN recognition system for a curvature primal sketch – NN based nonlinear temporal-spatial noise rejection system – relaxation rate for improving Hopfield network – Oja's NN and influence of the learning gain on its dynamics Genetic algorithms – theory and applications: transposition: a biological-inspired mechanism to use with GAs (= genetic algorithms) – GA for decision tree induction – optimising decision classifications using GAs – scheduling tasks with intertask communication onto multiprocessors by GAs – design of robust networks with GA – effect of degenerate coding on GAs – multiple traffic signal control using a GA – evolving musical harmonisation – niched-penalty approach for constraint handling in GAs – GA with dynamic population size – GA with dynamic niche clustering for multimodal function optimisation Soft computing and uncertainty: self-adaptation of evolutionary constructed decision trees by information spreading – evolutionary programming of near optimal NNs
Author | : P.J. Green |
Publisher | : CRC Press |
Total Pages | : 197 |
Release | : 1993-05-01 |
Genre | : Mathematics |
ISBN | : 1482229757 |
Download Nonparametric Regression and Generalized Linear Models Book in PDF, ePub and Kindle
Nonparametric Regression and Generalized Linear Models focuses on the roughness penalty method of nonparametric smoothing and shows how this technique provides a unifying approach to a wide range of smoothing problems. The emphasis is methodological rather than theoretical, and the authors concentrate on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students.