Advanced statistical methods for the analysis of large data-sets
(eBook)
Published:
Heidelberg ; New York : Springer, ©2012.
Format:
eBook
ISBN:
9783642210372, 3642210376, 3642210368, 9783642210365
Content Description:
1 online resource (xiii, 484 pages) : illustrations
Status:
Available Online
Description
Many research studies in the social and economic fields regard the collection and analysis of large amounts of data. These data sets vary in their nature and complexity, they may be one-off or repeated, they may be hierarchical, spatial or temporal. Examples include textual data, transaction-based data, medical data and financial time-series. Standard statistical techniques are usually not well suited to manage this type of data and many authors have proposed extensions of classical techniques or completely new methods. The huge size of these data-sets and their complexity require new strategies of analysis sometimes subsumed under the terms "data mining" or "predictive analytics". This volume contains a peer review selection of papers, whose preliminary version was presented at the international meeting of the Italian Statistical Society "Statistical Methods for the analysis of large data-sets". It collects new ideas, methods and original applications to deal with the complexity and high dimensionality of data
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APA Citation (style guide)
Di Ciaccio, A., Coli, M., & Angulo Ibañez, J. M. (2012). Advanced statistical methods for the analysis of large data-sets. Heidelberg ; New York, Springer.
Chicago / Turabian - Author Date Citation (style guide)Di Ciaccio, Agostino, Mauro, Coli and Jose Miguel, Angulo Ibañez. 2012. Advanced Statistical Methods for the Analysis of Large Data-sets. Heidelberg ; New York, Springer.
Chicago / Turabian - Humanities Citation (style guide)Di Ciaccio, Agostino, Mauro, Coli and Jose Miguel, Angulo Ibañez, Advanced Statistical Methods for the Analysis of Large Data-sets. Heidelberg ; New York, Springer, 2012.
MLA Citation (style guide)Di Ciaccio, Agostino,, et al. Advanced Statistical Methods for the Analysis of Large Data-sets. Heidelberg ; New York, Springer, 2012.
Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Language:
English
UPC:
10.1007/978-3-642-21037-2
Notes
Bibliography
Includes bibliographical references.
Description
Many research studies in the social and economic fields regard the collection and analysis of large amounts of data. These data sets vary in their nature and complexity, they may be one-off or repeated, they may be hierarchical, spatial or temporal. Examples include textual data, transaction-based data, medical data and financial time-series. Standard statistical techniques are usually not well suited to manage this type of data and many authors have proposed extensions of classical techniques or completely new methods. The huge size of these data-sets and their complexity require new strategies of analysis sometimes subsumed under the terms "data mining" or "predictive analytics". This volume contains a peer review selection of papers, whose preliminary version was presented at the international meeting of the Italian Statistical Society "Statistical Methods for the analysis of large data-sets". It collects new ideas, methods and original applications to deal with the complexity and high dimensionality of data
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acb5fcfa-e5d0-261f-e3e3-1bf54f90d8ff
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| Last File Modification Time | Apr 05, 2024 08:58:03 AM |
| Last Grouped Work Modification Time | Apr 05, 2024 08:52:37 AM |
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| 245 | 0 | 0 | |a Advanced statistical methods for the analysis of large data-sets /|c Agostino Di Ciaccio, Mauro Coli, Jose Miguel Angulo Ibañez, editors. |
| 260 | |a Heidelberg ;|a New York :|b Springer,|c ©2012. | ||
| 300 | |a 1 online resource (xiii, 484 pages) :|b illustrations | ||
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| 490 | 1 | |a Studies in theoretical and applied statistics. Selected papers of the Statistical Societies | |
| 504 | |a Includes bibliographical references. | ||
| 505 | 0 | 0 | |g Part 1.|t Clustering Large Data-Sets /|r Clustering Large Data Set: An Applied Comparative Study /|r Laura Bocci and Isabella Mingo --|t Clustering in Feature Space for Interesting Pattern Identification of Categorical Data /|r Marina Marino, Francesco Palumbo and Cristina Tortora --|t Clustering Geostatistical Functional Data /|r Elvira Romano and Rosanna Verde --|t Joint Clustering and Alignment of Functional Data: An Application to Vascular Geometries /|r Laura M. Sangalli, Piercesare Secchi, Simone Vantini and Valeria Vitelli --|g Part 2.|t Statistics in medicine /|r Bayesian Methods for Time Course Microarray Analysis: From Genes' Detection to Clustering /|r Claudia Angelini, Daniela De Canditiis and Marianna Pensky --|t Longitudinal Analysis of Gene Expression Profiles Using Functional Mixed-Effects Models /|r Maurice Berk, Cheryl Hemingway, Michael Levin and Giovanni Montana --|t A Permutation Solution to Compare Two Hepatocellular Carcinoma Markers /|r Agata Zirilli and Angela Alibrandi --|g Part 3.|t Integrating Administrative Data /|r Statistical Perspective on Blocking Methods When Linking Large Data-sets /|r Nicoletta Cibella and Tiziana Tuoto --|t Integrating Households Income Microdata in the Estimate of the Italian GDP /|r Alessandra Coli and Francesca Tartamella --|t The Employment Consequences of Globalization: Linking Data on Employers and Employees in the Netherlands /|r Fabienne Fortanier, Marjolein Korvorst and Martin Luppes --|t Applications of Bayesian Networks in Official Statistics /|r Paola Vicard and Mauro Scanu --|g Part 4.|t Outliers and Missing Data /|r A Correlated Random Effects Model for Longitudinal Data with Non-ignorable Drop-Out: An Application to University Student Performance /|r Filippo Belloc, Antonello Maruotti and Lea Petrella --|t Risk Analysis Approaches to Rank Outliers in Trade Data /|r Vytis Kopustinskas and Spyros Arsenis --|t Problems and Challenges in the Analysis of Complex Data: Static and Dynamic Approaches /|r Marco Riani, Anthony Atkinson and Andrea Cerioli. |
| 505 | 0 | 0 | |t Ensemble Support Vector Regression:A New Non-parametric Approach for Multiple Imputation /|r Daria Scacciatelli --|g Part 5.|t Time Series Analysis /|r On the Use of PLS Regression for Forecasting Large Sets of Cointegrated Time Series /|r Gianluca Cubadda and Barbara Guardabascio --|t Large-Scale Portfolio Optimisation with Heuristics /|r Manfred Gilli and Enrico Schumann --|t Detecting Short-Term Cycles in Complex Time Series Databases /|r F. Giordano, M.L. Parrella and M. Restaino --|t Assessing the Beneficial Effects of Economic Growth: The Harmonic Growth Index /|r Daria Mendola and Raffaele Scuderi --|t Time Series Convergence within I(2) Models: the Case of Weekly Long Term Bond Yields in the Four Largest Euro Area Countries /|r Giuliana Passamani --|g Part 6.|t Environmental Statistics /|r Anthropogenic CO2 Emissions and Global Warming: Evidence from Granger Causality Analysis /|r Massimo Bilancia and Domenico Vitale --|t Temporal and Spatial Statistical Methods to Remove External Effects on Groundwater Levels /|r Daniele Imparato, Andrea Carena and Mauro Gasparini --|t Reduced Rank Covariances for the Analysis of Environmental Data /|r Orietta Nicolis and Doug Nychka --|t Radon Level in Dwellings and Uranium Content in Soil in the Abruzzo Region: A Preliminary Investigation by Geographically Weighted Regression /|r Eugenia Nissi, Annalina Sarra and Sergio Palermi --|g Part 7.|t Probability and density estimation /|r Applications of Large Deviations to Hidden Markov Chains Estimation /|r M. Greco Del Fabiola --|t Multivariate Tail Dependence Coefficients for Archimedean Copulae /|r Giovanni De Luca and Giorgia Rivieccio --|t A Note on Density Estimation for Circular Data /|r Marco Di Marzio, Agnese Panzera and Charles C. Taylor --|t Markov Bases for Sudoku Grids /|r Roberto Fontana, Fabio Rapallo and Maria Piera Rogantin --|g Part 8.|t Application in Economics /|r Estimating the Probability of Moonlighting in Italian Building Industry /|r Maria Felice Arezzo and Giorgio Alleva. |
| 505 | 0 | 0 | |t Use of Interactive Plots and Tables for Robust Analysis of International Trade Data /|r Domenico Perrotta and Francesca Torti --|t Generational Determinants on the Employment Choice in Italy /|r Claudio Quintano, Rosalia Castellano and Gennaro Punzo --|t Route-Based Performance Evaluation Using Data Envelopment Analysis Combined with Principal Component Analysis /|r Agnese Rapposelli --|g Part 9.|t WEB and Text Mining /|r Web Surveys: Methodological Problems and Research Perspectives /|r Silvia Biffignandi and Jelke Bethlehem --|t Semantic Based DCM Models for Text Classification /|r Paola Cerchiello --|t Probabilistic Relational Models for Operational Risk: A New Application Area and an Implementation Using Domain Ontologies /|r Marcus Spies --|g Part 10.|t Advances on surveys /|r Efficient Statistical Sample Designs in a GIS for Monitoring the Landscape Changes /|r Elisabetta Carfagna, Patrizia Tassinari, Maroussa Zagoraiou, Stefano Benni and Daniele Torreggiani --|t Studying Foreigners' Migration Flows Through a Network Analysis Approach /|r Cinzia Conti, Domenico Gabrielli, Antonella Guarneri and Enrico Tucci --|t Estimation of Income Quantiles at the Small Area Level in Tuscany /|r Caterina Giusti, Stefano Marchetti and Monica Pratesi --|t The Effects of Socioeconomic Background and Test-taking Motivation on Italian Students' Achievement /|r Claudio Quintano, Rosalia Castellano and Sergio Longobardi --|g Part 11.|t Multivariate Analysis /|r Firm Size Dynamics in an Industrial District: The Mover-Stayer Model in Action /|r F. Cipollini, C. Ferretti and P. Ganugi --|t Multiple Correspondence Analysis for the Quantification and Visualization of Large Categorical Data Sets /|r Alfonso Iodice D'Enza and Michael Greenacre --|t Multivariate Ranks-Based Concordance Indexes /|r Emanuela Raffinetti and Paolo Giudici --|t Methods for Reconciling the Micro and the Macro in Family Demography Research: A Systematisation /|r Anna Matysiak and Daniele Vignoli. |
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