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Ridges in Image and Data Analysis, D. Eberly


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Цена: 16769.00р.
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Автор: D. Eberly
Название:  Ridges in Image and Data Analysis
ISBN: 9780792342687
Издательство: Springer
Классификация:

ISBN-10: 0792342682
Обложка/Формат: Hardcover
Страницы: 215
Вес: 0.50 кг.
Дата издания: 30.09.1996
Серия: Computational Imaging and Vision
Язык: English
Размер: 234 x 156 x 14
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Providing a thorough development of ridges and their application to image and data analysis, this includes chapters on the formal ridge definitions in any geometric setting, and a chapter on the numerical implementation, and applications chapter covers: medical image analysis, molecular modeling, and analysis of fluid flow.


Analysis of longitudinal data

Название: Analysis of longitudinal data
ISBN: 0199676755 ISBN-13(EAN): 9780199676750
Издательство: Oxford Academ
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Цена: 8395.00 р.
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Описание: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.

Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis

Автор: Wayne L. Myers; Ganapati P. Patil
Название: Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis
ISBN: 1441942718 ISBN-13(EAN): 9781441942715
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This book describes an integrated approach to using remotely sensed data in conjunction with geographic information systems for landscape analysis. Remotely sensed data are compressed into an analytical image-map that is compatible with the most popular geographic information systems as well as freeware viewers.

Bayesian Data Analysis, Third Edition

Автор: Gelman
Название: Bayesian Data Analysis, Third Edition
ISBN: 1439840954 ISBN-13(EAN): 9781439840955
Издательство: Taylor&Francis
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Цена: 11088.00 р.
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Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Categorical Data Analysis

Автор: Agresti Alan
Название: Categorical Data Analysis
ISBN: 0470463635 ISBN-13(EAN): 9780470463635
Издательство: Wiley
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Цена: 20109.00 р.
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Описание: Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis. " Statistics in Medicine "It is a total delight reading this book.

Ridges in Image and Data Analysis

Автор: D. Eberly
Название: Ridges in Image and Data Analysis
ISBN: 9048147611 ISBN-13(EAN): 9789048147618
Издательство: Springer
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Цена: 16769.00 р.
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Описание: The concept of ridges has appeared numerous times in the image processing liter- ature. The con- cept of ridge as a manifold of critical points is a natural extension of the concept of local maximum as an isolated critical point.

Theory of Ridge Regression Estimators with Applica tions

Автор: Saleh
Название: Theory of Ridge Regression Estimators with Applica tions
ISBN: 1118644611 ISBN-13(EAN): 9781118644614
Издательство: Wiley
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Цена: 16466.00 р.
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Описание:

This book discusses current methods of estimation in linearmodels. In particular, the authors address the methodology oflinear multiple regression models that plays an important role inalmost every scientific investigations in various fields, including economics, engineering, and biostatistics. Thestandard estimation method for regression parameters is theordinary least square (OLS) principal where residual squared errorsare minimized. Applied statisticians are often not satisfied withOLS estimators when the design matrix is ill-conditioned, leadingto a multicollinearity problem and large variances that make the"prediction" inaccurate. This book details theridge regression estimator, which was developed to combat themulticollinearity problem. Another estimator, called theLiu-estimator due to Liu Kejian, is also addressed since itprovides a competing resolution to the multicollinearityproblem. The ridge regression estimators are complicatednon-linear functions of the ridge parameter, whereas, theLiu estimators are a linear function of the shrinkage parameter.With a focus on the ridge regression and LIU estimators, this bookprovides expanded coverage beyond the usual preliminary test andStein type estimator. In this case, we propose a class of compositeestimators that are obtained by multiplying the OLS, restrictedOLS, preliminary test OLS, and Stein-type OLS by the "ridgefactor" and "Liu-factor." This research is asignificant step towards the study of dominance properties as wellas the comparison of the extent of LASSO properties. In addition, research materials involving shrinkage and model selection forlinear regression models are provided. Topical coverageincludes: preliminaries; linear regression models; multipleregression models; measurement error models; generalized linearmodels; and autoregressive Gaussian processes.

Astronomical Image and Data Analysis

Автор: J.-L. Starck; F. Murtagh
Название: Astronomical Image and Data Analysis
ISBN: 3642433537 ISBN-13(EAN): 9783642433535
Издательство: Springer
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Цена: 19564.00 р.
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Описание: to Applications and Methods.- Filtering.- Deconvolution.- Detection.- Image Compression.- Multichannel Data.- An Entropic Tour of Astronomical Data Analysis.- Astronomical Catalog Analysis.- Multiple Resolution in Data Storage and Retrieval.- Towards the Virtual Observatory.

Data Management and Internet Computing for Image/Pattern Analysis

Автор: David D. Zhang; Xiaobo Li; Zhiyong Liu
Название: Data Management and Internet Computing for Image/Pattern Analysis
ISBN: 1461355982 ISBN-13(EAN): 9781461355984
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Data Management and Internet Computing for Image/Pattern Analysis focuses on the data management issues and Internet computing aspect of image processing and pattern recognition research.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

Analysis of Multivariate and High-Dimensional Data

Автор: Koch
Название: Analysis of Multivariate and High-Dimensional Data
ISBN: 0521887933 ISBN-13(EAN): 9780521887939
Издательство: Cambridge Academ
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Цена: 10613.00 р.
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Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.

Quantitative Data Analysis

Автор: Willem Mertens and Amedeo Pugliese
Название: Quantitative Data Analysis
ISBN: 3319426990 ISBN-13(EAN): 9783319426990
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions. It provides readers with a basic understanding of the steps that each method involves, and of the facets of the analysis that require special attention. Rather than presenting an exhaustive overview of the methods or explaining them in detail, the book serves as a starting point for developing data analysis skills: it provides hands-on guidelines for conducting the most common analyses and reporting results, and includes pointers to more extensive resources. Comprehensive yet succinct, the book is brief and written in a language that everyone can understand - from students to those employed by organizations wanting to study the context in which they work. It also serves as a refresher for researchers who have learned data analysis techniques previously but who need a reminder for the specific study they are involved in.

Bayesian Nonparametric Data Analysis

Автор: Muller, P., Quintana, F.A., Jara, A., Hanson, T.
Название: Bayesian Nonparametric Data Analysis
ISBN: 3319189670 ISBN-13(EAN): 9783319189673
Издательство: Springer
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Цена: 11878.00 р.
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Описание: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.


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