Spline Models for Observational Data

Download Spline Models for Observational Data PDF Online Free

Author :
Publisher :
ISBN 13 :
Total Pages : 169 pages
Book Rating : 4.:/5 (115 download)

DOWNLOAD NOW!


Book Synopsis Spline Models for Observational Data by : Grace Wahba

Download or read book Spline Models for Observational Data written by Grace Wahba and published by . This book was released on 1990 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Spline Models for Observational Data

Download Spline Models for Observational Data PDF Online Free

Author :
Publisher : SIAM
ISBN 13 : 9781611970128
Total Pages : 181 pages
Book Rating : 4.9/5 (71 download)

DOWNLOAD NOW!


Book Synopsis Spline Models for Observational Data by : Grace Wahba

Download or read book Spline Models for Observational Data written by Grace Wahba and published by SIAM. This book was released on 1990-01-01 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download Spline Models for Observational Data PDF Online Free

Author :
Publisher : SIAM
ISBN 13 : 0898712440
Total Pages : 174 pages
Book Rating : 4.8/5 (987 download)

DOWNLOAD NOW!


Book Synopsis Spline Models for Observational Data by : Grace Wahba

Download or read book Spline Models for Observational Data written by Grace Wahba and published by SIAM. This book was released on 1990-09-01 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Theory and Computational Aspects of Smoothing

Download Statistical Theory and Computational Aspects of Smoothing PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3642484255
Total Pages : 265 pages
Book Rating : 4.6/5 (424 download)

DOWNLOAD NOW!


Book Synopsis Statistical Theory and Computational Aspects of Smoothing by : Wolfgang Härdle

Download or read book Statistical Theory and Computational Aspects of Smoothing written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download Smoothing Spline ANOVA Models PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 9781489989840
Total Pages : 0 pages
Book Rating : 4.9/5 (898 download)

DOWNLOAD NOW!


Book Synopsis Smoothing Spline ANOVA Models by : Chong Gu

Download or read book Smoothing Spline ANOVA Models written by Chong Gu and published by Springer. This book was released on 2015-06-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Nonparametric Regression and Spline Smoothing, Second Edition

Download Nonparametric Regression and Spline Smoothing, Second Edition PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 9780824793371
Total Pages : 368 pages
Book Rating : 4.7/5 (933 download)

DOWNLOAD NOW!


Book Synopsis Nonparametric Regression and Spline Smoothing, Second Edition by : Randall L. Eubank

Download or read book Nonparametric Regression and Spline Smoothing, Second Edition written by Randall L. Eubank and published by CRC Press. This book was released on 1999-02-09 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Spline Regression Models

Download Spline Regression Models PDF Online Free

Author :
Publisher : SAGE
ISBN 13 : 9780761924203
Total Pages : 86 pages
Book Rating : 4.9/5 (242 download)

DOWNLOAD NOW!


Book Synopsis Spline Regression Models by : Lawrence C. Marsh

Download or read book Spline Regression Models written by Lawrence C. Marsh and published by SAGE. This book was released on 2001-09-14 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spline Regression Models shows how to use dummy variables to formulate and estimate spline regression models both in situations where the number and location of the spline knots are known in advance, and where estimation is required.

Smoothness Priors Analysis of Time Series

Download Smoothness Priors Analysis of Time Series PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1461207614
Total Pages : 265 pages
Book Rating : 4.4/5 (612 download)

DOWNLOAD NOW!


Book Synopsis Smoothness Priors Analysis of Time Series by : Genshiro Kitagawa

Download or read book Smoothness Priors Analysis of Time Series written by Genshiro Kitagawa and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smoothness Priors Analysis of Time Series addresses some of the problems of modeling stationary and nonstationary time series primarily from a Bayesian stochastic regression "smoothness priors" state space point of view. Prior distributions on model coefficients are parametrized by hyperparameters. Maximizing the likelihood of a small number of hyperparameters permits the robust modeling of a time series with relatively complex structure and a very large number of implicitly inferred parameters. The critical statistical ideas in smoothness priors are the likelihood of the Bayesian model and the use of likelihood as a measure of the goodness of fit of the model. The emphasis is on a general state space approach in which the recursive conditional distributions for prediction, filtering, and smoothing are realized using a variety of nonstandard methods including numerical integration, a Gaussian mixture distribution-two filter smoothing formula, and a Monte Carlo "particle-path tracing" method in which the distributions are approximated by many realizations. The methods are applicable for modeling time series with complex structures.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

Download Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide PDF Online Free

Author :
Publisher : Government Printing Office
ISBN 13 : 1587634236
Total Pages : 236 pages
Book Rating : 4.5/5 (876 download)

DOWNLOAD NOW!


Book Synopsis Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide by : Agency for Health Care Research and Quality (U.S.)

Download or read book Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Bayesian Regression Modeling with INLA

Download Bayesian Regression Modeling with INLA PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1351165755
Total Pages : 312 pages
Book Rating : 4.3/5 (511 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Regression Modeling with INLA by : Xiaofeng Wang

Download or read book Bayesian Regression Modeling with INLA written by Xiaofeng Wang and published by CRC Press. This book was released on 2018-01-29 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of the posterior marginal distributions need to be drawn using INLA, so it is a computationally convenient alternative to Markov chain Monte Carlo (MCMC), the standard tool for Bayesian inference. Bayesian Regression Modeling with INLA covers a wide range of modern regression models and focuses on the INLA technique for building Bayesian models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to demonstrate the interplay of theory and practice with reproducible studies. Complete R commands are provided for each example, and a supporting website holds all of the data described in the book. An R package including the data and additional functions in the book is available to download. The book is aimed at readers who have a basic knowledge of statistical theory and Bayesian methodology. It gets readers up to date on the latest in Bayesian inference using INLA and prepares them for sophisticated, real-world work. Xiaofeng Wang is Professor of Medicine and Biostatistics at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University and a Full Staff in the Department of Quantitative Health Sciences at Cleveland Clinic. Yu Ryan Yue is Associate Professor of Statistics in the Paul H. Chook Department of Information Systems and Statistics at Baruch College, The City University of New York. Julian J. Faraway is Professor of Statistics in the Department of Mathematical Sciences at the University of Bath.

Semiparametric Regression with R

Download Semiparametric Regression with R PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 1493988530
Total Pages : 341 pages
Book Rating : 4.4/5 (939 download)

DOWNLOAD NOW!


Book Synopsis Semiparametric Regression with R by : Jaroslaw Harezlak

Download or read book Semiparametric Regression with R written by Jaroslaw Harezlak and published by Springer. This book was released on 2018-12-12 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts. The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R.

Curves and Surfaces

Download Curves and Surfaces PDF Online Free

Author :
Publisher : Academic Press
ISBN 13 : 1483263878
Total Pages : 535 pages
Book Rating : 4.4/5 (832 download)

DOWNLOAD NOW!


Book Synopsis Curves and Surfaces by : Pierre-Jean Laurent

Download or read book Curves and Surfaces written by Pierre-Jean Laurent and published by Academic Press. This book was released on 2014-05-12 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Curves and Surfaces provides information pertinent to the fundamental aspects of approximation theory with emphasis on approximation of images, surface compression, wavelets, and tomography. This book covers a variety of topics, including error estimates for multiquadratic interpolation, spline manifolds, and vector spline approximation. Organized into 77 chapters, this book begins with an overview of the method, based on a local Taylor expansion of the final curve, for computing the parameter values. This text then presents a vector approximation based on general spline function theory. Other chapters consider a nonparametric technique for estimating under random censorship the amplitude of a change point in change point hazard models. This book discusses as well the algorithm for ray tracing rational parametric surfaces based on inversion and implicitization. The final chapter deals with the results concerning the norm of the interpolation operator and error estimates for a square domain. This book is a valuable resource for mathematicians.

Statistical Advances in the Biomedical Sciences

Download Statistical Advances in the Biomedical Sciences PDF Online Free

Author :
Publisher : John Wiley & Sons
ISBN 13 : 0470181192
Total Pages : 623 pages
Book Rating : 4.4/5 (71 download)

DOWNLOAD NOW!


Book Synopsis Statistical Advances in the Biomedical Sciences by : Atanu Biswas

Download or read book Statistical Advances in the Biomedical Sciences written by Atanu Biswas and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research and the sophisticated advances in computing, it has become essential for practitioners in the biomedical sciences to be fully educated on the role statistics plays in ensuring the accurate analysis of research findings. Statistical Advances in the Biomedical Sciences explores the growing value of statistical knowledge in the management and comprehension of medical research and, more specifically, provides an accessible introduction to the contemporary methodologies used to understand complex problems in the four major areas of modern-day biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Composed of contributions from eminent researchers in the field, this volume discusses the application of statistical techniques to various aspects of modern medical research and illustrates how these methods ultimately prove to be an indispensable part of proper data collection and analysis. A structural uniformity is maintained across all chapters, each beginning with an introduction that discusses general concepts and the biomedical problem under focus and is followed by specific details on the associated methods, algorithms, and applications. In addition, each chapter provides a summary of the main ideas and offers a concluding remarks section that presents novel ideas, approaches, and challenges for future research. Complete with detailed references and insight on the future directions of biomedical research, Statistical Advances in the Biomedical Sciences provides vital statistical guidance to practitioners in the biomedical sciences while also introducing statisticians to new, multidisciplinary frontiers of application. This text is an excellent reference for graduate- and PhD-level courses in various areas of biostatistics and the medical sciences and also serves as a valuable tool for medical researchers, statisticians, public health professionals, and biostatisticians.

Nonparametric and Semiparametric Models

Download Nonparametric and Semiparametric Models PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 9783540207221
Total Pages : 340 pages
Book Rating : 4.2/5 (72 download)

DOWNLOAD NOW!


Book Synopsis Nonparametric and Semiparametric Models by : Wolfgang Härdle

Download or read book Nonparametric and Semiparametric Models written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2004-03-22 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.

Total Least Squares and Errors-in-Variables Modeling

Download Total Least Squares and Errors-in-Variables Modeling PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 9401735522
Total Pages : 389 pages
Book Rating : 4.4/5 (17 download)

DOWNLOAD NOW!


Book Synopsis Total Least Squares and Errors-in-Variables Modeling by : S. van Huffel

Download or read book Total Least Squares and Errors-in-Variables Modeling written by S. van Huffel and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: In response to a growing interest in Total Least Squares (TLS) and Errors-In-Variables (EIV) modeling by researchers and practitioners, well-known experts from several disciplines were invited to prepare an overview paper and present it at the third international workshop on TLS and EIV modeling held in Leuven, Belgium, August 27-29, 2001. These invited papers, representing two-thirds of the book, together with a selection of other presented contributions yield a complete overview of the main scientific achievements since 1996 in TLS and Errors-In-Variables modeling. In this way, the book nicely completes two earlier books on TLS (SIAM 1991 and 1997). Not only computational issues, but also statistical, numerical, algebraic properties are described, as well as many new generalizations and applications. Being aware of the growing interest in these techniques, it is a strong belief that this book will aid and stimulate users to apply the new techniques and models correctly to their own practical problems.

Machine Learning

Download Machine Learning PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1466583339
Total Pages : 458 pages
Book Rating : 4.4/5 (665 download)

DOWNLOAD NOW!


Book Synopsis Machine Learning by : Stephen Marsland

Download or read book Machine Learning written by Stephen Marsland and published by CRC Press. This book was released on 2014-10-08 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students

Semiparametric Regression for the Social Sciences

Download Semiparametric Regression for the Social Sciences PDF Online Free

Author :
Publisher : John Wiley & Sons
ISBN 13 : 9780470998120
Total Pages : 230 pages
Book Rating : 4.9/5 (981 download)

DOWNLOAD NOW!


Book Synopsis Semiparametric Regression for the Social Sciences by : Luke John Keele

Download or read book Semiparametric Regression for the Social Sciences written by Luke John Keele and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology via a selection of carefully explained examples and data sets. It also demonstrates the potential of these techniques using detailed empirical examples drawn from the social and political sciences. Each chapter includes exercises and examples and there is a supplementary website containing all the datasets used, as well as computer code, allowing readers to replicate every analysis reported in the book. Includes software for implementing the methods in S-Plus and R.