Statistical Theory And Computational Aspects Of Smoothing

Author : Wolfgang Härdle,Michael Schimek
Publisher : Springer Science & Business Media
Page : 265 pages
File Size : 40,9 Mb
Release : 2013-03-08
Category : Business & Economics
ISBN : 9783642484254

Get Book

Statistical Theory and Computational Aspects of Smoothing by Wolfgang Härdle,Michael Schimek Pdf

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 : Wolfgang Hardle,Michael Schimek
Publisher : Unknown
Page : 276 pages
File Size : 43,9 Mb
Release : 1996-05-15
Category : Electronic
ISBN : 3642484263

Get Book

Statistical Theory and Computational Aspects of Smoothing by Wolfgang Hardle,Michael Schimek Pdf

Author : Jeffrey S. Simonoff
Publisher : Springer Science & Business Media
Page : 349 pages
File Size : 42,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461240266

Get Book

Smoothing Methods in Statistics by Jeffrey S. Simonoff Pdf

Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics. It will thus be of particular interest to data analysts, as arguments generally proceed from actual data rather than statistical theory, while the "Background Material" sections will interest statisticians studying the field. Over 750 references allow researchers to find the original sources for more details, and the "Computational Issues" sections provide sources for statistical software that use the methods discussed. Each chapter includes exercises with a heavily computational focus based upon the data sets used in the book, making it equally suitable as a textbook for a course in smoothing.

Author : Yuichi Mori
Publisher : Springer Science & Business Media
Page : 1096 pages
File Size : 51,8 Mb
Release : 2004-07-14
Category : Computers
ISBN : 3540404643

Get Book

Handbook of Computational Statistics by Yuichi Mori Pdf

The Handbook of Computational Statistics: Concepts and Methodology is divided into four parts. It begins with an overview over the field of Computational Statistics. The second part presents several topics in the supporting field of statistical computing. Emphasis is placed on the need of fast and accurate numerical algorithms and it discusses some of the basic methodologies for transformation, data base handling and graphics treatment. The third part focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Finally a set of selected applications like Bioinformatics, Medical Imaging, Finance and Network Intrusion Detection highlight the usefulness of computational statistics.

Author : James E. Gentle,Wolfgang Karl Härdle,Yuichi Mori
Publisher : Springer Science & Business Media
Page : 1180 pages
File Size : 49,8 Mb
Release : 2012-07-06
Category : Computers
ISBN : 9783642215513

Get Book

Handbook of Computational Statistics by James E. Gentle,Wolfgang Karl Härdle,Yuichi Mori Pdf

The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.

Author : Ivanka Horová,Jan Koláček,Jiří Zelinka
Publisher : World Scientific
Page : 244 pages
File Size : 52,8 Mb
Release : 2012-08-14
Category : Mathematics
ISBN : 9789814405508

Get Book

Kernel Smoothing in Matlab by Ivanka Horová,Jan Koláček,Jiří Zelinka Pdf

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 function, indices of quality and bivariate density. Specifically, methods for choosing a choice of the optimal bandwidth and a special procedure for simultaneous choice of the bandwidth, the kernel and its order are implemented. The toolbox is divided into six parts according to the chapters of the book. All scripts are included in a user interface and it is easy to manipulate with this interface. Each chapter of the book contains a detailed help for the related part of the toolbox too. This book is intended for newcomers to the field of smoothing techniques and would also be appropriate for a wide audience: advanced graduate, PhD students and researchers from both the statistical science and interface disciplines. Contents:IntroductionUnivariate Kernel Density EstimationKernel Estimation of a Distribution FunctionKernel Estimation and Reliability AssessmentKernel Estimation of a Hazard FunctionKernel Estimation of a Regression FunctionMultivariate Kernel Density Estimation Readership: Advanced graduate students, researchers in mathematics or statistics. Keywords:Kernel;Bandwidth;Density Estimate;Kernel Regression;Hazard FunctionKey Features:Toolbox in MatlabBrief overview of existing methodsDeveloping a new unifying bandwidth selection method

Author : Geof H. Givens,Jennifer A. Hoeting
Publisher : John Wiley & Sons
Page : 496 pages
File Size : 48,5 Mb
Release : 2012-10-09
Category : Mathematics
ISBN : 9781118555484

Get Book

Computational Statistics by Geof H. Givens,Jennifer A. Hoeting Pdf

This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

Author : Ivanka Horova,Jan Kolacek,Jiri Zelinka
Publisher : World Scientific
Page : 242 pages
File Size : 51,6 Mb
Release : 2012
Category : Mathematics
ISBN : 9789814405492

Get Book

Kernel Smoothing in MATLAB by Ivanka Horova,Jan Kolacek,Jiri Zelinka Pdf

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 function, indices of quality and bivariate density. Specifically, methods for choosing a choice of the optimal bandwidth and a special procedure for simultaneous choice of the bandwidth, the kernel and its order are implemented. The toolbox is divided into six parts according to the chapters of the book.All scripts are included in a user interface and it is easy to manipulate with this interface. Each chapter of the book contains a detailed help for the related part of the toolbox too. This book is intended for newcomers to the field of smoothing techniques and would also be appropriate for a wide audience: advanced graduate, PhD students and researchers from both the statistical science and interface disciplines.

Author : James E. Gentle
Publisher : Springer Science & Business Media
Page : 420 pages
File Size : 49,9 Mb
Release : 2006-04-18
Category : Computers
ISBN : 9780387216119

Get Book

Elements of Computational Statistics by James E. Gentle Pdf

Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books

Author : Paul-Andre Monney
Publisher : Springer Science & Business Media
Page : 160 pages
File Size : 55,5 Mb
Release : 2013-04-18
Category : Business & Economics
ISBN : 9783642517464

Get Book

A Mathematical Theory of Arguments for Statistical Evidence by Paul-Andre Monney Pdf

The subject of this book is the reasoning under uncertainty based on sta tistical evidence, where the word reasoning is taken to mean searching for arguments in favor or against particular hypotheses of interest. The kind of reasoning we are using is composed of two aspects. The first one is inspired from classical reasoning in formal logic, where deductions are made from a knowledge base of observed facts and formulas representing the domain spe cific knowledge. In this book, the facts are the statistical observations and the general knowledge is represented by an instance of a special kind of sta tistical models called functional models. The second aspect deals with the uncertainty under which the formal reasoning takes place. For this aspect, the theory of hints [27] is the appropriate tool. Basically, we assume that some uncertain perturbation takes a specific value and then logically eval uate the consequences of this assumption. The original uncertainty about the perturbation is then transferred to the consequences of the assumption. This kind of reasoning is called assumption-based reasoning. Before going into more details about the content of this book, it might be interesting to look briefly at the roots and origins of assumption-based reasoning in the statistical context. In 1930, R. A. Fisher [17] defined the notion of fiducial distribution as the result of a new form of argument, as opposed to the result of the older Bayesian argument.

Author : Artur Gramacki
Publisher : Springer
Page : 176 pages
File Size : 48,7 Mb
Release : 2017-12-21
Category : Technology & Engineering
ISBN : 9783319716886

Get Book

Nonparametric Kernel Density Estimation and Its Computational Aspects by Artur Gramacki Pdf

This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. The theory of KDE appears to have matured and is now well developed and understood. However, there is not much progress observed in terms of performance improvements. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects. The book contains both some background and much more sophisticated material, hence also more experienced researchers in the KDE area may find it interesting. The presented material is richly illustrated with many numerical examples using both artificial and real datasets. Also, a number of practical applications related to KDE are presented.

Author : Mikis D. Stasinopoulos,Robert A. Rigby,Gillian Z. Heller,Vlasios Voudouris,Fernanda De Bastiani
Publisher : CRC Press
Page : 549 pages
File Size : 45,8 Mb
Release : 2017-04-21
Category : Mathematics
ISBN : 9781351980388

Get Book

Flexible Regression and Smoothing by Mikis D. Stasinopoulos,Robert A. Rigby,Gillian Z. Heller,Vlasios Voudouris,Fernanda De Bastiani Pdf

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent. In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that the response variable has any parametric (continuous, discrete or mixed) distribution which might be heavy- or light-tailed, and positively or negatively skewed. In addition, all the parameters of the distribution (location, scale, shape) can be modelled as linear or smooth functions of explanatory variables. Key Features: Provides a broad overview of flexible regression and smoothing techniques to learn from data whilst also focusing on the practical application of methodology using GAMLSS software in R. Includes a comprehensive collection of real data examples, which reflect the range of problems addressed by GAMLSS models and provide a practical illustration of the process of using flexible GAMLSS models for statistical learning. R code integrated into the text for ease of understanding and replication. Supplemented by a website with code, data and extra materials. This book aims to help readers understand how to learn from data encountered in many fields. It will be useful for practitioners and researchers who wish to understand and use the GAMLSS models to learn from data and also for students who wish to learn GAMLSS through practical examples.

Author : R.A. Thisted
Publisher : Routledge
Page : 297 pages
File Size : 42,6 Mb
Release : 2017-10-19
Category : Mathematics
ISBN : 9781351452748

Get Book

Elements of Statistical Computing by R.A. Thisted Pdf

Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.

Author : Ludwig Fahrmeir,Gerhard Tutz
Publisher : Springer Science & Business Media
Page : 537 pages
File Size : 42,6 Mb
Release : 2013-03-14
Category : Mathematics
ISBN : 9781475734546

Get Book

Multivariate Statistical Modelling Based on Generalized Linear Models by Ludwig Fahrmeir,Gerhard Tutz Pdf

The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.

Author : Cristina Davino,Marilena Furno,Domenico Vistocco
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 42,7 Mb
Release : 2013-12-31
Category : Mathematics
ISBN : 9781119975281

Get Book

Quantile Regression by Cristina Davino,Marilena Furno,Domenico Vistocco Pdf

A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensive description of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and followed by applications using real data. Quantile Regression: Presents a complete treatment of quantile regression methods, including, estimation, inference issues and application of methods. Delivers a balance between methodolgy and application Offers an overview of the recent developments in the quantile regression framework and why to use quantile regression in a variety of areas such as economics, finance and computing. Features a supporting website (www.wiley.com/go/quantile_regression) hosting datasets along with R, Stata and SAS software code. Researchers and PhD students in the field of statistics, economics, econometrics, social and environmental science and chemistry will benefit from this book.