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Author : Scientific Meeting of the Classification and Data Analysis Group
Publisher : Unknown
Page : 439 pages
File Size : 53,6 Mb
Release : 2021
Category : Electronic
ISBN : 8855183419
Author : Giovanni C. Porzio,Carla Rampichini,Chiara Bocci
Publisher : Firenze University Press
Page : 455 pages
File Size : 45,6 Mb
Release : 2024-05-11
Category : Business & Economics
ISBN : 9788855183406
The book collects the short papers presented at the 13th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS). The meeting has been organized by the Department of Statistics, Computer Science and Applications of the University of Florence, under the auspices of the Italian Statistical Society and the International Federation of Classification Societies (IFCS). CLADAG is a member of the IFCS, a federation of national, regional, and linguistically-based classification societies. It is a non-profit, non-political scientific organization, whose aims are to further classification research.
Author : Nicola Salvati,Cira Perna,Stefano Marchetti,Raymond Chambers
Publisher : Springer Nature
Page : 548 pages
File Size : 46,7 Mb
Release : 2023-02-14
Category : Mathematics
ISBN : 9783031166099
This book includes a wide selection of papers presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS2021), held virtually on 21-25 June 2021. It covers a wide variety of subjects ranging from methodological and theoretical contributions to applied works and case studies, giving an excellent overview of the interests of the Italian statisticians and their international collaborations. Intended for researchers interested in theoretical and empirical issues, this volume provides interesting starting points for further research.
Author : Classification Group of SIS. Meeting
Publisher : Unknown
Page : 378 pages
File Size : 53,8 Mb
Release : 1999
Category : Electronic books
ISBN : OCLC:1269045014
International Federation of Classification Societies The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a· range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America -CSNA; Gesellschaft fUr Klassifikation -GfKl; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - COSIS; Societe Francophone de Classification -SFC. Now the IFCS includes the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Section - SKAD; Portuguese Classification Association - CLAD; Group-at-Large; Korean Classification Society -KCS. Biannual Meeting of the Classification and Data Analysis Group of SIS The biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica (SIS) was held in Pescara, July 3 -4, 1997. The 69 papers presented were divided in 17 sessions. Each session was organized by a chairperson with two invited speakers and two contributed papers from a call for papers. All the works were referred. Furthermore, during the meeting a discussant was provided for each session. A short version of the papers (4 pages) was.published before the conference.
Author : Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publisher : Springer Nature
Page : 357 pages
File Size : 53,9 Mb
Release : 2021
Category : Application software
ISBN : 9783030668914
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Author : Fabrizio Durante,Carlo Sempi
Publisher : CRC Press
Page : 331 pages
File Size : 45,7 Mb
Release : 2015-07-01
Category : Mathematics
ISBN : 9781439884447
Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas in a variety of applications. Throughout the book, historical remarks and further readings highlight active research in the field, including new results, streamlined presentations, and new proofs of old results.After covering the
Author : Michael Greenacre,Jorg Blasius
Publisher : CRC Press
Page : 607 pages
File Size : 40,5 Mb
Release : 2006-06-23
Category : Mathematics
ISBN : 9781420011319
As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su
Author : Paolo Giudici
Publisher : John Wiley & Sons
Page : 379 pages
File Size : 46,5 Mb
Release : 2005-09-27
Category : Computers
ISBN : 9780470871393
Data mining can be defined as the process of selection, explorationand modelling of large databases, in order to discover models andpatterns. The increasing availability of data in the currentinformation society has led to the need for valid tools for itsmodelling and analysis. Data mining and applied statistical methodsare the appropriate tools to extract such knowledge from data.Applications occur in many different fields, including statistics,computer science, machine learning, economics, marketing andfinance. This book is the first to describe applied data mining methodsin a consistent statistical framework, and then show how they canbe applied in practice. All the methods described are eithercomputational, or of a statistical modelling nature. Complexprobabilistic models and mathematical tools are not used, so thebook is accessible to a wide audience of students and industryprofessionals. The second half of the book consists of nine casestudies, taken from the author's own work in industry, thatdemonstrate how the methods described can be applied to realproblems. Provides a solid introduction to applied data mining methods ina consistent statistical framework Includes coverage of classical, multivariate and Bayesianstatistical methodology Includes many recent developments such as web mining,sequential Bayesian analysis and memory based reasoning Each statistical method described is illustrated with real lifeapplications Features a number of detailed case studies based on appliedprojects within industry Incorporates discussion on software used in data mining, withparticular emphasis on SAS Supported by a website featuring data sets, software andadditional material Includes an extensive bibliography and pointers to furtherreading within the text Author has many years experience teaching introductory andmultivariate statistics and data mining, and working on appliedprojects within industry A valuable resource for advanced undergraduate and graduatestudents of applied statistics, data mining, computer science andeconomics, as well as for professionals working in industry onprojects involving large volumes of data - such as in marketing orfinancial risk management.
Author : Charles Bouveyron,Gilles Celeux,T. Brendan Murphy,Adrian E. Raftery
Publisher : Cambridge University Press
Page : 446 pages
File Size : 54,5 Mb
Release : 2019-07-25
Category : Business & Economics
ISBN : 9781108494205
Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.
Author : Mariana Montiel,Francisco Gomez-Martin,Octavio A. Agustín-Aquino
Publisher : Springer
Page : 0 pages
File Size : 44,5 Mb
Release : 2019-05-31
Category : Language Arts & Disciplines
ISBN : 3030213919
This book constitutes the thoroughly refereed proceedings of the 7th International Conference on Mathematics and Computation in Music, MCM 2019, held in Madrid, Spain, in June 2019. The 22 full papers and 10 short papers presented were carefully reviewed and selected from 48 submissions. The papers feature research that combines mathematics or computation with music theory, music analysis, composition, and performance. They are organized in topical sections on algebraic and other abstract mathematical approaches to understanding musical objects; remanaging Riemann: mathematical music theory as “experimental philosophy”?; octave division; computer-based approaches to composition and score structuring; models for music cognition and beat tracking; pedagogy of mathematical music theory. The chapter “Distant Neighbors and Interscalar Contiguities” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author : Paolo Giudici,Silvia Figini
Publisher : John Wiley & Sons
Page : 277 pages
File Size : 53,9 Mb
Release : 2009-05-26
Category : Mathematics
ISBN : 9780470058862
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.
Author : Alan Agresti
Publisher : John Wiley & Sons
Page : 471 pages
File Size : 50,8 Mb
Release : 2015-02-23
Category : Mathematics
ISBN : 9781118730034
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.
Author : Rainer Bruggemann,Lars Carlsen,Tugce Beycan,Christian Suter,Filomena Maggino
Publisher : Springer Nature
Page : 324 pages
File Size : 49,5 Mb
Release : 2021-03-01
Category : Science
ISBN : 9783030596835
Indicators are more and more applied to describe and analyze complex systems. Typical examples: Innovation potential of nations, child-well being, Environmental health, poverty, chemical pollution, corruption of nations. The task is: How can a system of indicators be defined in order to fulfill the above expectations. One possibility is the application of the mathematical theory of partial order, especially when the indicator system shall be used for ranking purposes.
Author : Annarita Franza,Johannes Mattes,Giovanni Pratesi
Publisher : Firenze University Press
Page : 284 pages
File Size : 46,9 Mb
Release : 2022-02-24
Category : Nature
ISBN : 9788855184939
This work is the critical edition of the catalog of Holy Roman Emperor Leopold’s II mineralogical collection. The volume, unpublished and preserved at the Historical Archives of the University of Firenze Museum System, dates to 1765 and describes 242 mineralogical specimens coming primarily from the current Slovak-Hungarian mining district. This edition gives the transcription of the German manuscript and its translation into English together with an organized system of notation to illustrate the complex history of the text, the characterization of the mineralogical species, and the geographical location of the mineral extraction sites. This work represents to date the only published catalog of a mineralogical collection belonging to a member of the Habsburg-Lorraine family.
Author : Sophie Dabo-Niang,Frédéric Ferraty
Publisher : Physica
Page : 0 pages
File Size : 55,7 Mb
Release : 2010-10-21
Category : Mathematics
ISBN : 3790825603
An increasing number of statistical problems and methods involve infinite-dimensional aspects. This is due to the progress of technologies which allow us to store more and more information while modern instruments are able to collect data much more effectively due to their increasingly sophisticated design. This evolution directly concerns statisticians, who have to propose new methodologies while taking into account such high-dimensional data (e.g. continuous processes, functional data, etc.). The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile. This book gathers important contributions on the functional and operatorial statistics fields.