Advances In Complex Data Modeling And Computational Methods In Statistics

Author : Anna Maria Paganoni,Piercesare Secchi
Publisher : Springer
Page : 210 pages
File Size : 49,6 Mb
Release : 2014-11-04
Category : Mathematics
ISBN : 9783319111490

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Advances in Complex Data Modeling and Computational Methods in Statistics by Anna Maria Paganoni,Piercesare Secchi Pdf

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Author : Pietro Mantovan,Piercesare Secchi
Publisher : Springer Science & Business Media
Page : 170 pages
File Size : 43,5 Mb
Release : 2011-01-27
Category : Computers
ISBN : 9788847013865

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Complex Data Modeling and Computationally Intensive Statistical Methods by Pietro Mantovan,Piercesare Secchi Pdf

Selected from the conference "S.Co.2009: Complex Data Modeling and Computationally Intensive Methods for Estimation and Prediction," these 20 papers cover the latest in statistical methods and computational techniques for complex and high dimensional datasets.

Author : Anonim
Publisher : Unknown
Page : 176 pages
File Size : 45,6 Mb
Release : 2011-08-14
Category : Electronic
ISBN : 8847013925

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Complex Data Modeling and Computationally Intensive Statistical Methods by Anonim Pdf

Author : Matteo Grigoletto,Francesco Lisi,Sonia Petrone
Publisher : Springer Science & Business Media
Page : 228 pages
File Size : 49,5 Mb
Release : 2013-01-26
Category : Mathematics
ISBN : 9788847028715

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Complex Models and Computational Methods in Statistics by Matteo Grigoletto,Francesco Lisi,Sonia Petrone Pdf

The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.

Author : Germán Aneiros,Ivana Horová,Marie Hušková,Philippe Vieu
Publisher : Springer Nature
Page : 254 pages
File Size : 40,8 Mb
Release : 2020-06-19
Category : Mathematics
ISBN : 9783030477561

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Functional and High-Dimensional Statistics and Related Fields by Germán Aneiros,Ivana Horová,Marie Hušková,Philippe Vieu Pdf

This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.

Author : Barry C. Arnold,N. Balakrishnan,Jose-Maria Sarabia Alegria,Roberto Minguez
Publisher : Springer Science & Business Media
Page : 374 pages
File Size : 40,6 Mb
Release : 2009-04-09
Category : Mathematics
ISBN : 9780817646264

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Advances in Mathematical and Statistical Modeling by Barry C. Arnold,N. Balakrishnan,Jose-Maria Sarabia Alegria,Roberto Minguez Pdf

Enrique Castillo is a leading figure in several mathematical and engineering fields. Organized to honor Castillo’s significant contributions, this volume is an outgrowth of the "International Conference on Mathematical and Statistical Modeling," and covers recent advances in the field. Applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques are presented.

Author : John M. Chambers
Publisher : John Wiley & Sons
Page : 302 pages
File Size : 41,7 Mb
Release : 1977
Category : Mathematical statistics
ISBN : UCAL:B2504933

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Computational Methods for Data Analysis by John M. Chambers Pdf

Programming; Data management and manipulation; Numerical computations; Linear models; Nonlinear models; Simulation of Random processes; Computational graphics.

Author : Noel Cressie,Christopher K. Wikle
Publisher : John Wiley & Sons
Page : 624 pages
File Size : 47,8 Mb
Release : 2015-11-02
Category : Mathematics
ISBN : 9781119243069

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Statistics for Spatio-Temporal Data by Noel Cressie,Christopher K. Wikle Pdf

Winner of the 2013 DeGroot Prize. A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods Noel Cressie and Christopher K. Wikle, are also winners of the 2011 PROSE Award in the Mathematics category, for the book “Statistics for Spatio-Temporal Data” (2011), published by John Wiley and Sons. (The PROSE awards, for Professional and Scholarly Excellence, are given by the Association of American Publishers, the national trade association of the US book publishing industry.) Statistics for Spatio-Temporal Data has now been reprinted with small corrections to the text and the bibliography. The overall content and pagination of the new printing remains the same; the difference comes in the form of corrections to typographical errors, editing of incomplete and missing references, and some updated spatio-temporal interpretations. From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models. Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes. Topics of coverage include: Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Author : Paola Pucci,Fabio Manfredini,Paolo Tagliolato
Publisher : Springer
Page : 94 pages
File Size : 44,9 Mb
Release : 2015-02-18
Category : Science
ISBN : 9783319148335

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Mapping Urban Practices Through Mobile Phone Data by Paola Pucci,Fabio Manfredini,Paolo Tagliolato Pdf

This book explains the potential value of using mobile phone data to monitor urban practices and identify rhythms of use in today’s cities. Drawing upon research conducted in the Italian region of Lombardy, the authors demonstrate how maps based on mobile phone data, which are better tailored to the dynamic processes at work in cities, can document urban practices, provide new insights into spatial and temporal patterns of mobility, and assist in recognizing different communities of practice. The described methodology permits detailed visualization of the spatial distribution of mobility flows and offers a more extensive and refined description of the distribution of urban activity than is provided by traditional travel surveys. The book also details how maps derived by processing mobile phone data can assist in the definition of urban policies that will deliver services that match cities’ needs, facilitate the management of large events (inflow, outflow, and monitoring), and reflect time-dependent phenomena not included in traditional analyses.

Author : Lodhi, Huma,Yamanishi, Yoshihiro
Publisher : IGI Global
Page : 418 pages
File Size : 51,9 Mb
Release : 2010-07-31
Category : Computers
ISBN : 9781615209125

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Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques by Lodhi, Huma,Yamanishi, Yoshihiro Pdf

"This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.

Author : Paola Pucci,Matteo Colleoni
Publisher : Springer
Page : 274 pages
File Size : 50,5 Mb
Release : 2015-12-08
Category : Science
ISBN : 9783319225784

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Understanding Mobilities for Designing Contemporary Cities by Paola Pucci,Matteo Colleoni Pdf

This book explores mobilities as a key to understanding the practices that both frame and generate contemporary everyday life in the urban context. At the same time, it investigates the challenges arising from the interpretation of mobility as a socio-spatial phenomenon both in the social sciences and in urban studies. Leading sociologists, economists, urban planners and architects address the ways in which spatial mobilities contribute to producing diversified uses of the city and describe forms and rhythms of different life practices, including unexpected uses and conflicts. The individual sections of the book focus on the role of mobility in transforming contemporary cities; the consequences of interpreting mobility as a socio-spatial phenomenon for urban projects and policies; the conflicts and inequalities generated by the co-presence of different populations due to mobility and by the interests gathered around major mobility projects; and the use of new data and mapping of mobilities to enhance comprehension of cities. The theoretical discussion is complemented by references to practical experiences, helping readers gain a broader understanding of mobilities in relation to the capacity to analyze, plan and design contemporary cities.

Author : Alex Karagrigoriou,Christina Parpoula,Yannis Dimotikalis,Christos H. Skiadas
Publisher : John Wiley & Sons
Page : 304 pages
File Size : 55,9 Mb
Release : 2021-03-31
Category : Business & Economics
ISBN : 9781119821571

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Applied Modeling Techniques and Data Analysis 1 by Alex Karagrigoriou,Christina Parpoula,Yannis Dimotikalis,Christos H. Skiadas Pdf

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.

Author : Dirk P. Kroese,Joshua C.C. Chan
Publisher : Springer Science & Business Media
Page : 412 pages
File Size : 44,6 Mb
Release : 2013-11-18
Category : Computers
ISBN : 9781461487753

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Statistical Modeling and Computation by Dirk P. Kroese,Joshua C.C. Chan Pdf

This textbook on statistical modeling and statistical inference will assist advanced undergraduate and graduate students. Statistical Modeling and Computation provides a unique introduction to modern Statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of Mathematical Statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. Each of the three parts will cover topics essential to university courses. Part I covers the fundamentals of probability theory. In Part II, the authors introduce a wide variety of classical models that include, among others, linear regression and ANOVA models. In Part III, the authors address the statistical analysis and computation of various advanced models, such as generalized linear, state-space and Gaussian models. Particular attention is paid to fast Monte Carlo techniques for Bayesian inference on these models. Throughout the book the authors include a large number of illustrative examples and solved problems. The book also features a section with solutions, an appendix that serves as a MATLAB primer, and a mathematical supplement.​

Author : Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu
Publisher : Springer
Page : 222 pages
File Size : 51,6 Mb
Release : 2016-11-30
Category : Mathematics
ISBN : 9789811025945

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Advanced Statistical Methods in Data Science by Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu Pdf

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Author : Etienne de Rocquigny
Publisher : John Wiley & Sons
Page : 483 pages
File Size : 54,5 Mb
Release : 2012-04-12
Category : Mathematics
ISBN : 9781119941651

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Modelling Under Risk and Uncertainty by Etienne de Rocquigny Pdf

Modelling has permeated virtually all areas of industrial, environmental, economic, bio-medical or civil engineering: yet the use of models for decision-making raises a number of issues to which this book is dedicated: How uncertain is my model ? Is it truly valuable to support decision-making ? What kind of decision can be truly supported and how can I handle residual uncertainty ? How much refined should the mathematical description be, given the true data limitations ? Could the uncertainty be reduced through more data, increased modeling investment or computational budget ? Should it be reduced now or later ? How robust is the analysis or the computational methods involved ? Should / could those methods be more robust ? Does it make sense to handle uncertainty, risk, lack of knowledge, variability or errors altogether ? How reasonable is the choice of probabilistic modeling for rare events ? How rare are the events to be considered ? How far does it make sense to handle extreme events and elaborate confidence figures ? Can I take advantage of expert / phenomenological knowledge to tighten the probabilistic figures ? Are there connex domains that could provide models or inspiration for my problem ? Written by a leader at the crossroads of industry, academia and engineering, and based on decades of multi-disciplinary field experience, Modelling Under Risk and Uncertainty gives a self-consistent introduction to the methods involved by any type of modeling development acknowledging the inevitable uncertainty and associated risks. It goes beyond the “black-box” view that some analysts, modelers, risk experts or statisticians develop on the underlying phenomenology of the environmental or industrial processes, without valuing enough their physical properties and inner modelling potential nor challenging the practical plausibility of mathematical hypotheses; conversely it is also to attract environmental or engineering modellers to better handle model confidence issues through finer statistical and risk analysis material taking advantage of advanced scientific computing, to face new regulations departing from deterministic design or support robust decision-making. Modelling Under Risk and Uncertainty: Addresses a concern of growing interest for large industries, environmentalists or analysts: robust modeling for decision-making in complex systems. Gives new insights into the peculiar mathematical and computational challenges generated by recent industrial safety or environmental control analysis for rare events. Implements decision theory choices differentiating or aggregating the dimensions of risk/aleatory and epistemic uncertainty through a consistent multi-disciplinary set of statistical estimation, physical modelling, robust computation and risk analysis. Provides an original review of the advanced inverse probabilistic approaches for model identification, calibration or data assimilation, key to digest fast-growing multi-physical data acquisition. Illustrated with one favourite pedagogical example crossing natural risk, engineering and economics, developed throughout the book to facilitate the reading and understanding. Supports Master/PhD-level course as well as advanced tutorials for professional training Analysts and researchers in numerical modeling, applied statistics, scientific computing, reliability, advanced engineering, natural risk or environmental science will benefit from this book.