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Multivariate Dispersion Central Regions And Depth
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Book Synopsis Multivariate Dispersion, Central Regions, and Depth by : Karl Mosler
Download or read book Multivariate Dispersion, Central Regions, and Depth written by Karl Mosler and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has many applications to stochastic comparison problems in economics and other fields. It covers theory of lift zonoids and demonstrates its usefulness in multivariate analysis, an informal introduction to basic ideas, and a comprehensive investigation into the theory, as well as various applications of the lift zonoid approach and may be separately studied. Readers are assumed to have a firm grounding in probability at the graduate level.
Book Synopsis Multivariate Dispersion, Central Regions, and Depth by : Karl Mosler
Download or read book Multivariate Dispersion, Central Regions, and Depth written by Karl Mosler and published by . This book was released on 2011-04-01 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Depth written by Regina Y. Liu and published by American Mathematical Soc.. This book was released on 2006 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of some of the research presented at the workshop of the same name held in May 2003 at Rutgers University. The workshop brought together researchers from two different communities: statisticians and specialists in computational geometry. The main idea unifying these two research areas turned out to be the notion of data depth, which is an important notion both in statistics and in the study of efficiency of algorithms used in computational geometry. Many of the articles in the book lay down the foundations for further collaboration and interdisciplinary research. Information for our distributors: Co-published with the Center for Discrete Mathematics and Theoretical Computer Science beginning with Volume 8. Volumes 1-7 were co-published with the Association for Computer Machinery (ACM).
Book Synopsis Robustness and Complex Data Structures by : Claudia Becker
Download or read book Robustness and Complex Data Structures written by Claudia Becker and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Festschrift in honour of Ursula Gather’s 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.
Book Synopsis Combining Soft Computing and Statistical Methods in Data Analysis by : Christian Borgelt
Download or read book Combining Soft Computing and Statistical Methods in Data Analysis written by Christian Borgelt and published by Springer Science & Business Media. This book was released on 2010-10-12 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.
Book Synopsis Case Studies in Bayesian Statistics by : Constantine Gatsonis
Download or read book Case Studies in Bayesian Statistics written by Constantine Gatsonis and published by Springer. This book was released on 2018-08-17 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains invited case studies with the accompanying discussion as well as contributed papers selected by a refereeing process of 6th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University in October, 2001.
Book Synopsis Statistical Matching by : Susanne Rässler
Download or read book Statistical Matching written by Susanne Rässler and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Government policy questions and media planning tasks may be answered by this data set. It covers a wide range of different aspects of statistical matching that in Europe typically is called data fusion. A book about statistical matching will be of interest to researchers and practitioners, starting with data collection and the production of public use micro files, data banks, and data bases. People in the areas of database marketing, public health analysis, socioeconomic modeling, and official statistics will find it useful.
Author :Miguel Concepcion Lopez-Diaz Publisher :Springer Science & Business Media ISBN 13 :3540444653 Total Pages :769 pages Book Rating :4.5/5 (44 download)
Book Synopsis Soft Methodology and Random Information Systems by : Miguel Concepcion Lopez-Diaz
Download or read book Soft Methodology and Random Information Systems written by Miguel Concepcion Lopez-Diaz and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of experimental data resulting from some underlying random process is a fundamental part of most scientific research. Probability Theory and Statistics have been developed as flexible tools for this analyis, and have been applied successfully in various fields such as Biology, Economics, Engineering, Medicine or Psychology. However, traditional techniques in Probability and Statistics were devised to model only a singe source of uncertainty, namely randomness. In many real-life problems randomness arises in conjunction with other sources, making the development of additional "softening" approaches essential. This book is a collection of papers presented at the 2nd International Conference on Soft Methods in Probability and Statistics (SMPS’2004) held in Oviedo, providing a comprehensive overview of the innovative new research taking place within this emerging field.
Book Synopsis Data Analysis, Machine Learning and Knowledge Discovery by : Myra Spiliopoulou
Download or read book Data Analysis, Machine Learning and Knowledge Discovery written by Myra Spiliopoulou and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012.
Book Synopsis Weighted Empirical Processes in Dynamic Nonlinear Models by : Hira L. Koul
Download or read book Weighted Empirical Processes in Dynamic Nonlinear Models written by Hira L. Koul and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a unified approach for obtaining the limiting distributions of minimum distance. It discusses classes of goodness-of-t tests for fitting an error distribution in some of these models and/or fitting a regression-autoregressive function without assuming the knowledge of the error distribution. The main tool is the asymptotic equi-continuity of certain basic weighted residual empirical processes in the uniform and L2 metrics.
Book Synopsis Recent Advances in Data Mining of Enterprise Data by : Thunshun Warren Liao
Download or read book Recent Advances in Data Mining of Enterprise Data written by Thunshun Warren Liao and published by World Scientific. This book was released on 2008 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as ?enterprise data?. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.
Book Synopsis Multivariate Nonparametric Methods with R by : Hannu Oja
Download or read book Multivariate Nonparametric Methods with R written by Hannu Oja and published by Springer Science & Business Media. This book was released on 2010-03-25 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory. Hannu Oja is an academy professor and a professor in biometry in the University of Tampere. He has authored and coauthored numerous research articles in multivariate nonparametrical and robust methods as well as in biostatistics.
Book Synopsis Pandemics: Insurance and Social Protection by : María del Carmen Boado-Penas
Download or read book Pandemics: Insurance and Social Protection written by María del Carmen Boado-Penas and published by Springer Nature. This book was released on 2022 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic. Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing in the presence of low probability events, group testing, compositional data analysis for detecting data inconsistencies, behaviouristic aspects in fighting a pandemic, and insurers' legal problems, amongst others. Concluding with an essay by a practicing actuary on the applicability of the methods proposed, this interdisciplinary book is aimed at actuaries as well as readers with a background in mathematics, economics, statistics, finance, epidemiology, or sociology.
Book Synopsis Support Vector Machines by : Ingo Steinwart
Download or read book Support Vector Machines written by Ingo Steinwart and published by Springer Science & Business Media. This book was released on 2008-09-15 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the?eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.
Book Synopsis Quantile Regression by : Roger Koenker
Download or read book Quantile Regression written by Roger Koenker and published by Cambridge University Press. This book was released on 2005-05-05 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.
Book Synopsis Asymptotic Methods in Stochastics by : M. Csörgö
Download or read book Asymptotic Methods in Stochastics written by M. Csörgö and published by American Mathematical Soc.. This book was released on 2004 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Honoring over forty years of Miklos Csorgo's work in probability and statistics, this title shows the state of the research. This book covers such topics as: path properties of stochastic processes, weak convergence of random size sums, almost sure stability of weighted maxima, and procedures for detecting changes in statistical models.
Book Synopsis Advances on Income Inequality and Concentration Measures by : Gianni Betti
Download or read book Advances on Income Inequality and Concentration Measures written by Gianni Betti and published by Routledge. This book was released on 2008-04-24 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This impressive collection from some of today‘s leading distributional analysts provides an overview a wide range of economic, statistical and sociological relationships that have been opened up for scientific study by the work of two turn-of-the-20th-century economists: C. Gini and M. O. Lorenz. The authors include such figues as Barry A
