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Statistics - Statistical Theory and Methods | Advanced Statistical Methods for the Analysis of Large Data-Sets

Advanced Statistical Methods for the Analysis of Large Data-Sets

Di Ciaccio, Agostino, Coli, Mauro, Angulo Ibanez, Jose Miguel (Eds.)

2012, XIV, 486 p.

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  • Selected papers considering both methodological and applicative issues Analyzing several aspects of the following topics:
  • The treatment of large administrative data with data integration and record linkage
  • The analysis of genomic and microarray data
  • The visualization and reduction of large data-sets
  • The analysis of high frequency data in finance
  • The analysis of social networks or complex time series databases
  •  The analysis of environmental data

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.

Content Level » Research

Keywords » Clustering for large data-sets - Data Mining - Data integration and record linkage - Large-scale forecasting - Managing huge administrative data

Related subjects » Business, Economics & Finance - Computational Statistics - Statistical Theory and Methods

Table of contents 

Part I Clustering Large Data-Sets: Clustering Large Data Set: An Applied Comparative Study (Bocci L., Mingo I.).- Clustering in Feature Space for Interesting Pattern Identification of Categorical Data (Marino M., Palumbo F., Tortora C.).- Clustering geostatistical functional data (Romano E., Verde R.).-Joint Clustering and Alignment of Functional Data: An Application to Vascu-lar Geometries (Sangalli L.M., Secchi P., Vantini S., Vitelli V.).- Part II  Statistics in Medicine: Bayesian Methods for Time Course Microarray Analysis: From Genes’ Detection to Clustering (Angelini C., De Canditiis D., Pensky M.).- Longitudinal Analysis of Gene Expression Profiles Using Functional Mixed-effects Models (Berk M., Montana G., Levin M.,  Hemingway C.).- A Permutation Solution to Compare two Hepatocellular Carcinoma Markers (Zirilli A., Alibrandi A.).- Part III  Integrating Administrative Data: Statistical Perspective on Blocking Methods when Linking Large Data-Sets (Cibella N., Tuoto T.).- Integrating Households Income Microdata in the Estimate of the Italian GDP (Coli A., Tartamella F.).- The Employment Consequences of Globalization: Linking Data on Employers and Employees in the Netherlands (Fortanier F., Korvorst M., Luppes M.).- Applications of Bayesian networks in Official Statistics (Vicard P., Scanu M.).- Part IV  Outliers and Missing Data: A Correlated Random Effects Model for Longitudinal Data with Non-ignorable Drop-out: An Application to University Student Performance (Belloc F., Maruotti A., Petrella L.).- Risk Analysis Approaches to rank Outliers in Trade Data (Kopustinskas V., Arsenis S.).- Problems and Challenges in the Analysis of Complex Data: Static and Dynamic Approaches (Riani M., Atkinson A., Cerioli A.).- Ensemble Support Vector Regression: A New Non-parametric Approach for Multiple Imputation (Scacciatelli D.).- Part V  Time Series Analysis: On the Use of PLS Regression for Forecasting Large Sets of Cointegrated Time Series (Cubadda G., Guardabascio B.).- Large-Scale Portfolio Optimisation with Heuristics (Gilli M., Schumann E.).- Detecting Short-Term Cycles in Complex Time Series Databases (Giordano F., Parrella M.L., Restaino M.).- Assessing the Beneficial Effects of Economic Growth: The Harmonic Growth Index (Mendola D., Scuderi R.).- Time Series Convergence within I(2) Models: The Case of Weekly Long Term Bond Yields in the four Largest Euro Area Countries (Passamani G.).- Part VI  Environmental Statistics: Anthropogenic CO2 Emissions and Global Warming: Evidence from Granger Causality Analysis (Bilancia M., Vitale D.).- Temporal and Spatial Statistical Methods to Remove External Effects on Groundwater Levels (Imparato D., Carena A., Gasparini M.).- Reduced Rank Covariances for the Analysis of Environmental Data (Nicolis O., Nychka D.).- Radon Level in Dwellings and Uranium Content in Soil in the Abruzzo Region: A Preliminary Investigation by Geographically Weighted Regression (Nissi E., Sarra A., Palermi S.).- Part VII  Probability and Density Estimation.-       Applications of Large Deviations to Hidden Markov Chains Estimations (Del Greco M.).- Multivariate Tail Dependence Coefficients for Archimedean Copulae (De Luca G., Rivieccio G.).- A Note on Density Estimation for Circular Data (Di Marzio M., Panzera A., Taylor C.C.).- Markov Bases for Sudoku Grids (Fontana R., Rapallo F., Rogantin M.P.).- Part VIII  Application in Economics: Estimating the Probability of Moonlighting in Italian Building Industry (Arezzo M.F., Alleva G.).- Use of Interactive Plots and Tables for Robust Analysis of International Trade Data (Perrotta D., Torti F.) Generational Determinants on the Employment Choice in Italy (Quintano C., Castellano R., Punzo G.).- Route-based Performance Evaluation Using Data Envelopment Analysis Combined with Principal Component Analysis (Rapposelli A.).- Part IX  WEB and Text Mining: Web Surveys: Methodological Problems and Research Perspectives (Biffignandi S., Bethlehem J.).- Semantic Based DCM Models for Text Classification (Cerchiello P.).- Probabilistic Relational Models for Operational Risk – A new Application Area and an Implementation Using Domain Ontologies (Spies M.).- Part X  Advances on Surveys.- Efficient Statistical Sample Designs in a GIS for Monitoring the Landscape Changes (Carfagna E., Tassinari P., Zagoraiou M., Benni S., Torreggiani D.).- Studying Foreigners’ Migration Flows Through a Network  Analysis Approach (Conti C., Gabrielli D., Guarneri A., Tucci E.).- Estimation of Income Quantiles at the Small Area Level in Tuscany (Giusti C., Marchetti S., Pratesi M.).- The Effects of Socioeconomic Background and Test-taking Motivation on Italian Students’ Achievement (Quintano C., Castellano L., Longobardi R.).- Part XI  Multivariate Analysis: Firm Size Dynamics in an Industrial District: The Mover–Stayer Model in Action (Cipollini F. , Ferretti C., Ganugi P.).- Multiple Correspondence Analysis for the Quantification and Visualization of Large Categorical Data Sets (Iodice D'Enza A., Greenacre M.).- Multivariate Ranks-based Concordance Indexes (Raffinetti E., Giudici P.).- Methods for Reconciling the Micro and the Macro in Family Demography Research: A Systematization (Matysiak A., Vignoli D.).          

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