Statistical Data Analysis Based On The L B1 S Norm And Related Methods
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Statistical Data Analysis Based On The L B1 S Norm And Related Methods
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Author : Yadolah Dodge
language : en
Publisher: Springer Science & Business Media
Release Date : 2002
Statistical Data Analysis Based On The L B1 S Norm And Related Methods written by Yadolah Dodge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Mathematics categories.
This volume contains a selection of invited papers, presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in Neuchâtel, Switzerland, from August 4–9, 2002. The contributions represent a clear evidence to the importance of development of theory, methods and applications related to the statistical data analysis based on the L1-norm.
Soft Methods In Probability Statistics And Data Analysis
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Author : Przemyslaw Grzegorzewski
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11
Soft Methods In Probability Statistics And Data Analysis written by Przemyslaw Grzegorzewski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Mathematics categories.
Classical probability theory and mathematical statistics appear sometimes too rigid for real life problems, especially while dealing with vague data or imprecise requirements. These problems have motivated many researchers to "soften" the classical theory. Some "softening" approaches utilize concepts and techniques developed in theories such as fuzzy sets theory, rough sets, possibility theory, theory of belief functions and imprecise probabilities, etc. Since interesting mathematical models and methods have been proposed in the frameworks of various theories, this text brings together experts representing different approaches used in soft probability, statistics and data analysis.
Simulation In Computational Finance And Economics Tools And Emerging Applications
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Author : Alexandrova-Kabadjova, Biliana
language : en
Publisher: IGI Global
Release Date : 2012-08-31
Simulation In Computational Finance And Economics Tools And Emerging Applications written by Alexandrova-Kabadjova, Biliana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-31 with Business & Economics categories.
Simulation has become a tool difficult to substitute in many scientific areas like manufacturing, medicine, telecommunications, games, etc. Finance is one of such areas where simulation is a commonly used tool; for example, we can find Monte Carlo simulation in many financial applications like market risk analysis, portfolio optimization, credit risk related applications, etc. Simulation in Computational Finance and Economics: Tools and Emerging Applications presents a thorough collection of works, covering several rich and highly productive areas of research including Risk Management, Agent-Based Simulation, and Payment Methods and Systems, topics that have found new motivations after the strong recession experienced in the last few years. Despite the fact that simulation is widely accepted as a prominent tool, dealing with a simulation-based project requires specific management abilities of the researchers. Economic researchers will find an excellent reference to introduce them to the computational simulation models. The works presented in this book can be used as an inspiration for economic researchers interested in creating their own computational models in their respective fields.
Statistics And Machine Learning Methods For Ehr Data
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Author : Hulin Wu
language : en
Publisher: CRC Press
Release Date : 2020-12-10
Statistics And Machine Learning Methods For Ehr Data written by Hulin Wu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-10 with Business & Economics categories.
The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.
New Perspectives In Statistical Modeling And Data Analysis
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Author : Salvatore Ingrassia
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-29
New Perspectives In Statistical Modeling And Data Analysis written by Salvatore Ingrassia and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-29 with Mathematics categories.
This volume provides recent research results in data analysis, classification and multivariate statistics and highlights perspectives for new scientific developments within these areas. Particular attention is devoted to methodological issues in clustering, statistical modeling and data mining. The volume also contains significant contributions to a wide range of applications such as finance, marketing, and social sciences. The papers in this volume were first presented at the 7th Conference of the Classification and Data Analysis Group (ClaDAG) of the Italian Statistical Society, held at the University of Catania, Italy.
Bayesian Data Analysis Third Edition
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2013-11-01
Bayesian Data Analysis Third Edition written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-01 with Mathematics categories.
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.
2022 Applied Mathematics And Statistics Editor S Pick
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Author : Charles K. Chui
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-06
2022 Applied Mathematics And Statistics Editor S Pick written by Charles K. Chui and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-06 with Science categories.
Journal Of The American Statistical Association
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Author :
language : en
Publisher:
Release Date : 2008
Journal Of The American Statistical Association written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Statistics categories.
All Of Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11
All Of Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Mathematics categories.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Signal Analysis
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Author : Ronald L. Allen
language : en
Publisher: John Wiley & Sons
Release Date : 2004-06-07
Signal Analysis written by Ronald L. Allen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-07 with Technology & Engineering categories.
Offers a well-rounded, mathematical approach to problems in signal interpretation using the latest time, frequency, and mixed-domain methods Equally useful as a reference, an up-to-date review, a learning tool, and a resource for signal analysis techniques Provides a gradual introduction to the mathematics so that the less mathematically adept reader will not be overwhelmed with instant hard analysis Covers Hilbert spaces, complex analysis, distributions, random signals, analog Fourier transforms, and more