Automatic Smoothing and Variable Selection Via Regularization

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Publisher :
ISBN 13 :
Total Pages : 112 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis Automatic Smoothing and Variable Selection Via Regularization by : Ming Yuan

Download or read book Automatic Smoothing and Variable Selection Via Regularization written by Ming Yuan and published by . This book was released on 2004 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Comparison of Regularization Methods for Variable Selection in Highly Correlated Data

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Comparison of Regularization Methods for Variable Selection in Highly Correlated Data by : 張靜萱

Download or read book Comparison of Regularization Methods for Variable Selection in Highly Correlated Data written by 張靜萱 and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational and Methodological Statistics and Biostatistics

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Publisher : Springer Nature
ISBN 13 : 3030421961
Total Pages : 543 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Computational and Methodological Statistics and Biostatistics by : Andriëtte Bekker

Download or read book Computational and Methodological Statistics and Biostatistics written by Andriëtte Bekker and published by Springer Nature. This book was released on 2020-08-10 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions;• Recent developments in supervised and unsupervised modelling;• Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.

Dissertation Abstracts International

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ISBN 13 :
Total Pages : 886 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Dissertation Abstracts International by :

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Big Data Analytics

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Publisher : Springer
ISBN 13 : 3319182846
Total Pages : 532 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Handbook of Big Data Analytics by : Wolfgang Karl Härdle

Download or read book Handbook of Big Data Analytics written by Wolfgang Karl Härdle and published by Springer. This book was released on 2018-07-20 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013

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Publisher : Springer
ISBN 13 : 3642407609
Total Pages : 708 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013 by : Kensaku Mori

Download or read book Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013 written by Kensaku Mori and published by Springer. This book was released on 2013-09-20 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 81 papers included in the third volume have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing; imaging, reconstruction, and enhancement; segmentation; physiological modeling, simulation, and planning; intraoperative guidance and robotics; microscope, optical imaging, and histology; diffusion MRI; brain segmentation and atlases; and functional MRI and neuroscience applications.

Semiparametric Theory and Missing Data

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Publisher : Springer Science & Business Media
ISBN 13 : 0387373454
Total Pages : 392 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Semiparametric Theory and Missing Data by : Anastasios Tsiatis

Download or read book Semiparametric Theory and Missing Data written by Anastasios Tsiatis and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.

Chemometrics with R

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Publisher : Springer Science & Business Media
ISBN 13 : 3642178413
Total Pages : 289 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Chemometrics with R by : Ron Wehrens

Download or read book Chemometrics with R written by Ron Wehrens and published by Springer Science & Business Media. This book was released on 2011-01-20 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R.

Statistical Applications of Linear Programming for Feature Selection Via Regularization Methods

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ISBN 13 :
Total Pages : 107 pages
Book Rating : 4.:/5 (275 download)

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Book Synopsis Statistical Applications of Linear Programming for Feature Selection Via Regularization Methods by : Yonggang Yao

Download or read book Statistical Applications of Linear Programming for Feature Selection Via Regularization Methods written by Yonggang Yao and published by . This book was released on 2008 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: We consider statistical procedures for feature selection defined by a family of regularization problems with convex piecewise linear loss functions and penalties of L_1 or L_infinity nature. For example, quantile regression and support vector machines with L_1 norm penalty fall into the category. Computationally, the regularization problems are linear programming (LP) problems indexed by a single parameter, which are known as "parametric cost LP" or "parametric right-hand-side LP" in the optimization theory. Their solution paths can be generated with certain simplex algorithms. This work exploits the connection between the family of regularization methods and the parametric LP theory and lays out a general simplex algorithm and its variant for generating regularized solution paths for the feature selection problems. The significance of such algorithms is that they allow a complete exploration of the model space along the paths and provide a broad view of persistent features in the data. The implications of the general path-finding algorithms are outlined for various statistical procedures, and they are illustrated with numerical examples.

Robust Statistics for Signal Processing

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Publisher : Cambridge University Press
ISBN 13 : 1107017416
Total Pages : 315 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Robust Statistics for Signal Processing by : Abdelhak M. Zoubir

Download or read book Robust Statistics for Signal Processing written by Abdelhak M. Zoubir and published by Cambridge University Press. This book was released on 2018-11-08 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the benefits of robust statistics for signal processing using this unique and authoritative text.

Machine Learning in Medical Imaging

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Publisher : Springer
ISBN 13 : 3642354289
Total Pages : 287 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Machine Learning in Medical Imaging by : Fei Wang

Download or read book Machine Learning in Medical Imaging written by Fei Wang and published by Springer. This book was released on 2012-11-13 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 33 revised full papers presented were carefully reviewed and selected from 67 submissions. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging. It focuses on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging.

Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing

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Publisher : John Wiley & Sons
ISBN 13 : 1118827074
Total Pages : 323 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing by : Jean-Francois Giovannelli

Download or read book Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing written by Jean-Francois Giovannelli and published by John Wiley & Sons. This book was released on 2015-02-02 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field’s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.

Foundations of Linear and Generalized Linear Models

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Publisher : John Wiley & Sons
ISBN 13 : 1118730305
Total Pages : 480 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Foundations of Linear and Generalized Linear Models by : Alan Agresti

Download or read book Foundations of Linear and Generalized Linear Models written by Alan Agresti and published by John Wiley & Sons. This book was released on 2015-01-15 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.

Statistica Sinica

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ISBN 13 :
Total Pages : 712 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Statistica Sinica by :

Download or read book Statistica Sinica written by and published by . This book was released on 2006 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt:

AI 2019: Advances in Artificial Intelligence

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Publisher : Springer Nature
ISBN 13 : 3030352889
Total Pages : 622 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis AI 2019: Advances in Artificial Intelligence by : Jixue Liu

Download or read book AI 2019: Advances in Artificial Intelligence written by Jixue Liu and published by Springer Nature. This book was released on 2019-11-25 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 32nd Australasian Joint Conference on Artificial Intelligence, AI 2019, held in Adelaide, SA, Australia, in December 2019. The 48 full papers presented in this volume were carefully reviewed and selected from 115 submissions. The paper were organized in topical sections named: game and multiagent systems; knowledge acquisition, representation, reasoning; machine learning and applications; natural language processing and text analytics; optimization and evolutionary computing; and image processing.

Statistical Learning with Sparsity

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Publisher : CRC Press
ISBN 13 : 1498712177
Total Pages : 354 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Statistical Learning with Sparsity by : Trevor Hastie

Download or read book Statistical Learning with Sparsity written by Trevor Hastie and published by CRC Press. This book was released on 2015-05-07 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underl

Gaussian Process Regression Analysis for Functional Data

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Publisher : CRC Press
ISBN 13 : 1439837740
Total Pages : 214 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Gaussian Process Regression Analysis for Functional Data by : Jian Qing Shi

Download or read book Gaussian Process Regression Analysis for Functional Data written by Jian Qing Shi and published by CRC Press. This book was released on 2011-07-01 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Coveri