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An Unbiased Estimator For The Roughness Of A Multivariate Gaussian Random Field
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Author :McGill University. Department of Mathematics and Statistics Publisher :Montréal : Department of Mathematics and Statistics, McGill University ISBN 13 : Total Pages :5 pages Book Rating :4.:/5 (363 download)
Book Synopsis An Unbiased Estimator for the Roughness of a Multivariate Gaussian Random Field by : McGill University. Department of Mathematics and Statistics
Download or read book An Unbiased Estimator for the Roughness of a Multivariate Gaussian Random Field written by McGill University. Department of Mathematics and Statistics and published by Montréal : Department of Mathematics and Statistics, McGill University. This book was released on 1996 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Neuroanatomy by : Moo K. Chung
Download or read book Computational Neuroanatomy written by Moo K. Chung and published by World Scientific. This book was released on 2013 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational neuroanatomy is an emerging field that utilizes various non-invasive brain imaging modalities, such as MRI and DTI, in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations. This discipline emerged about twenty years ago and has made substantial progress in the past decade. The main goals of this book are to provide an overview of various mathematical, statistical and computational methodologies used in the field to a wide range of researchers and students, and to address important yet technically challenging topics in further detail.
Book Synopsis Medical Image Databases by : Stephen T.C. Wong
Download or read book Medical Image Databases written by Stephen T.C. Wong and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services, education, and research. Authors were selected because they are doing cutting-edge basic or technology work in relevant areas. This was done to infuse each chapter with ideas from people actively investigating and developing medical image databases rather than simply review the existing literature. The authors have analyzed the literature and have expanded on their own research. They have also addressed several common threads within their generic topics. These include system architecture, standards, information retrieval, data modeling, image visualizations, query languages, telematics, data mining, and decision supports. The new ideas and results reported in this volume suggest new and better ways to develop imaging databases and possibly lead us to the next information infrastructure in biomedicine. Medical Image Databases is suitable as a textbook for a graduate-level course on biomedical imaging or medical image databases, and as a reference for researchers and practitioners in industry.
Book Synopsis Unbiased Estimators and their Applications by : V.G. Voinov
Download or read book Unbiased Estimators and their Applications written by V.G. Voinov and published by Springer Science & Business Media. This book was released on 1996-01-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a continuation of Unbiased Estimators and Their Applications, Vol. I: Univariate Case. It contains problems of parametric point estimation for multivariate probability distributions emphasizing problems of unbiased estimation. The volume consists of four chapters dealing, respectively, with some basic properties of multivariate continuous and discrete distributions, the general theory of point estimation in multivariate case, techniques for constructing unbiased estimators and applications of unbiased estimation theory in the multivariate case. These chapters contain numerous examples, many applications and are followed by a comprehensive Appendix which classifies and lists, in the form of tables, all known results relating to unbiased estimators of parameter functions for multivariate distributions. Audience: This volume will serve as a handbook on point unbiased estimation for researchers whose work involves statistics. It can also be recommended as a supplementary text for undergraduate and graduate students.
Book Synopsis Multivariate Gaussian Random Fields by : Yuzhen Zhou
Download or read book Multivariate Gaussian Random Fields written by Yuzhen Zhou and published by . This book was released on 2015 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Philosophical Transactions written by and published by . This book was released on 1999 with total page 1204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each issue of Transactions B is devoted to a specific area of the biological sciences, including clinical science. All papers are peer reviewed and edited to the highest standards. Published on the 29th of each month, Transactions B is essential reading for all biologists.
Book Synopsis Mathematical/computational Strategies for Analyzing 3D Human Brain Image Databases by : Paul Matthew Thompson
Download or read book Mathematical/computational Strategies for Analyzing 3D Human Brain Image Databases written by Paul Matthew Thompson and published by . This book was released on 1999 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Weighted Fourier Image Analysis and Modeling by : Shubing Wang
Download or read book Weighted Fourier Image Analysis and Modeling written by Shubing Wang and published by . This book was released on 2008 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Philosophical Transactions of the Royal Society of London by :
Download or read book Philosophical Transactions of the Royal Society of London written by and published by . This book was released on 1999 with total page 1030 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Effective Observation of Random Fields by : Wolfgang Näther
Download or read book Effective Observation of Random Fields written by Wolfgang Näther and published by . This book was released on 1985 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Maximum Likellhood Estimation of Covariance Parameters for Gaussian Random Fields by : C. R. Dietrich
Download or read book Maximum Likellhood Estimation of Covariance Parameters for Gaussian Random Fields written by C. R. Dietrich and published by . This book was released on 1989 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Design and Analysis of Computer Experiments by : Thomas J. Santner
Download or read book The Design and Analysis of Computer Experiments written by Thomas J. Santner and published by Springer. This book was released on 2019-01-08 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners
Download or read book Mathematical Reviews written by and published by . This book was released on 2003 with total page 1280 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Current Index to Statistics, Applications, Methods and Theory by :
Download or read book Current Index to Statistics, Applications, Methods and Theory written by and published by . This book was released on 1994 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
Book Synopsis Markov Random Fields in Image Segmentation by : Zoltan Kato
Download or read book Markov Random Fields in Image Segmentation written by Zoltan Kato and published by Now Pub. This book was released on 2012-09 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov Random Fields in Image Segmentation provides an introduction to the fundamentals of Markovian modeling in image segmentation as well as a brief overview of recent advances in the field. Segmentation is formulated within an image labeling framework, where the problem is reduced to assigning labels to pixels. In a probabilistic approach, label dependencies are modeled by Markov random fields (MRF) and an optimal labeling is determined by Bayesian estimation, in particular maximum a posteriori (MAP) estimation. The main advantage of MRF models is that prior information can be imposed locally through clique potentials. MRF models usually yield a non-convex energy function. The minimization of this function is crucial in order to find the most likely segmentation according to the MRF model. Classical optimization algorithms including simulated annealing and deterministic relaxation are treated along with more recent graph cut-based algorithms. The primary goal of this monograph is to demonstrate the basic steps to construct an easily applicable MRF segmentation model and further develop its multi-scale and hierarchical implementations as well as their combination in a multilayer model. Representative examples from remote sensing and biological imaging are analyzed in full detail to illustrate the applicability of these MRF models. Furthermore, a sample implementation of the most important segmentation algorithms is available as supplementary software. Markov Random Fields in Image Segmentation is an invaluable resource for every student, engineer, or researcher dealing with Markovian modeling for image segmentation.
Book Synopsis Random Surfaces by : Scott Sheffield
Download or read book Random Surfaces written by Scott Sheffield and published by . This book was released on 2005 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Density Estimation for Statistics and Data Analysis by : Bernard. W. Silverman
Download or read book Density Estimation for Statistics and Data Analysis written by Bernard. W. Silverman and published by Routledge. This book was released on 2018-02-19 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there has been a surge of interest in density estimation in recent years, much of the published research has been concerned with purely technical matters with insufficient emphasis given to the technique's practical value. Furthermore, the subject has been rather inaccessible to the general statistician. The account presented in this book places emphasis on topics of methodological importance, in the hope that this will facilitate broader practical application of density estimation and also encourage research into relevant theoretical work. The book also provides an introduction to the subject for those with general interests in statistics. The important role of density estimation as a graphical technique is reflected by the inclusion of more than 50 graphs and figures throughout the text. Several contexts in which density estimation can be used are discussed, including the exploration and presentation of data, nonparametric discriminant analysis, cluster analysis, simulation and the bootstrap, bump hunting, projection pursuit, and the estimation of hazard rates and other quantities that depend on the density. This book includes general survey of methods available for density estimation. The Kernel method, both for univariate and multivariate data, is discussed in detail, with particular emphasis on ways of deciding how much to smooth and on computation aspects. Attention is also given to adaptive methods, which smooth to a greater degree in the tails of the distribution, and to methods based on the idea of penalized likelihood.
