Studies in Theoretical and Applied Statistics (eBook)

SIS 2016, Salerno, Italy, June 8-10
eBook Download: PDF
2018 | 1st ed. 2018
XI, 347 Seiten
Springer International Publishing (Verlag)
978-3-319-73906-9 (ISBN)

Lese- und Medienproben

Studies in Theoretical and Applied Statistics -
Systemvoraussetzungen
96,29 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

This book includes a wide selection of the papers presented at the 48th Scientific Meeting of the Italian Statistical Society (SIS2016), held in Salerno on 8-10 June 2016. Covering a wide variety of topics ranging from modern data sources and survey design issues to measuring sustainable development, it provides a comprehensive overview of the current Italian scientific research in the fields of open data and big data in public administration and official statistics, survey sampling, ordinal and symbolic data, statistical models and methods for network data, time series forecasting, spatial analysis, environmental statistics, economic and financial data analysis, statistics in the education system, and sustainable development. Intended for researchers interested in theoretical and empirical issues, this volume provides interesting starting points for further research.



Cira Perna is currently Professor of Statistics and Head of the Department of Economics and Statistics, University of Salerno (Italy). Her research work mainly focuses on non-linear time series, artificial neural network models, and resampling techniques. She has published a number of papers in national and international journals on these topics, and she has been a member of the scientific committees of several national and international conferences.

Monica Pratesi is Professor of Statistics, University of Pisa, and holds the Jean Monnet Chair 'Small Area Methods for Monitoring of Poverty and Living Conditions in the EU' 2015-2017. She is the Director of the Tuscan Interuniversity Centre - Advanced Statistics for Equitable and Sustainable Development, entitled to Camilo Dagum. Her research interests include methods for survey sampling and analysis of survey data, small area estimation and design-based population inference. She has published a number of papers in national and international journals on these topics and has been a member of the scientific committees of several national and international conferences.

Anne Ruiz-Gazen is Professor of Applied Mathematics, specializing in statistics, and a member of the Toulouse School of Economics  - Research at University Toulouse 1 Capitole. Her areas of research include multivariate data analysis, survey sampling theory and, to a less extent, spatial econometrics and statistics. She has published more than fifty articles in refereed journals and books and has been a member of the scientific committees of several conferences.

Cira Perna is currently Professor of Statistics and Head of the Department of Economics and Statistics, University of Salerno (Italy). Her research work mainly focuses on non-linear time series, artificial neural network models, and resampling techniques. She has published a number of papers in national and international journals on these topics, and she has been a member of the scientific committees of several national and international conferences. Monica Pratesi is Professor of Statistics, University of Pisa, and holds the Jean Monnet Chair "Small Area Methods for Monitoring of Poverty and Living Conditions in the EU" 2015-2017. She is the Director of the Tuscan Interuniversity Centre - Advanced Statistics for Equitable and Sustainable Development, entitled to Camilo Dagum. Her research interests include methods for survey sampling and analysis of survey data, small area estimation and design-based population inference. She has published a number of papers in national and international journals on these topics and has been a member of the scientific committees of several national and international conferences. Anne Ruiz-Gazen is Professor of Applied Mathematics, specializing in statistics, and a member of the Toulouse School of Economics  - Research at University Toulouse 1 Capitole. Her areas of research include multivariate data analysis, survey sampling theory and, to a less extent, spatial econometrics and statistics. She has published more than fifty articles in refereed journals and books and has been a member of the scientific committees of several conferences.

1 C. Favre-Martinoz et al., Robustness in survey sampling using the conditional bias approach with R implementation.- 2 F. Andreis et al., Methodological perspectives for surveying rare and clustered population: towards a sequentially adaptive approach.- 3 M. L. Aversa et al., Age management in Italian companies. Findings from two INAPP surveys.- 4 M. Calzaroni et al., Generating high quality administrative data: new technologies in a national statistical reuse perspective.- 5 T. Tuoto et al., Exploring solutions for linking Big Data in Official Statistics.- 6 C. Franceschini and N. Loperfido, An Algorithm for Finding Projections with Extreme Kurtosis.- 7 L. Egidi et al., Maxima Units Search (MUS) algorithm: methodology and applications.- 8 D. Passaretti and D. Vistocco, DESPOTA: an algorithm to detect the partition in the extended hierarchy of a dendrogram.- 9 F. Pauli, The p-value case, a review of the debate: issues and plausible remedies.- 10 J. Koskinen et al., A dynamic discrete-choice model for movement flows.- 11 G. Ragozini et al., On the Analysis of Time-Varying Affiliation Networks: the Case of Stage Co-productions.- 12 M. Ichino and K. Umbleja, Similarity and Dissimilarity Measures for Mixed Feature-type Symbolic Data.- 13 L. D'Ambra et al., Dimensionality reduction methods for contingency tables with ordinal variables.- 14 R. Gerlach and G. Storti, Extended Realized GARCH models.- 15 L. Crosato and B. Zavanella, Updating CPI weights through compositional VAR forecasts: an application to the Italian index.- 16 P. Chirico, Prediction intervals for heteroscedastic series by Holt-Winters methods.- 17 F. Benassi et al., Measuring residential segregation of selected foreign groups with aspatial and spatial evenness indices. A case study.- 18 G. Adelfio et al., Space-time FPCA  clustering of multidimensional curves.- 19 D. Rocchini et al., The power of generalized entropy for biodiversity assessment by remote sensing: an open source approach.- 20 A. Lepore et al., An empirical approach to monitoring ship CO^2 emissions via Partial Least-Squares regression.- 21 A. Valentini et al., Promoting statistical literacy to university students: a new approach adopted by Istat.- 22 M. Enea, From South to North? Mobility of Southern Italian students at the transition from the first to the second level university degree.- 23 G. Leckie and H. Goldstein, Monitoring school performance using value-added and value-table models: Lessons from the UK.- 24 G. D'Epifanio, Indexing the Normalized Worthiness of Social Agents.- 25 E. Baldacci, Financial Crises and their Impacts: Data Gaps and Innovation in Statistical Production.- 26 A. Coli and B. Pacini, European welfare systems in official statistics: the national and local levels.- 27 M. Costa, Financial variables analysis by inequality decomposition.- 28 E. Grimaccia and T. Rondinella, A novel perspective in the analysis of sustainability, inclusion and smartness of growth through Europe 2020 indicators.- 29 I. Mingo et al., The Italian population behaviours toward environmental sustainability: a study from Istat surveys.- 30 C. Giusti and S. Marchetti, Estimating the at risk of poverty rate before and after social transfers at provincial level in Italy.

Erscheint lt. Verlag 3.4.2018
Reihe/Serie Springer Proceedings in Mathematics & Statistics
Springer Proceedings in Mathematics & Statistics
Zusatzinfo XI, 347 p. 72 illus., 47 illus. in color.
Verlagsort Cham
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Wirtschaft
Schlagworte Computational Statistics • Data Analysis • Demography • Public Statistics • Statistical Models
ISBN-10 3-319-73906-9 / 3319739069
ISBN-13 978-3-319-73906-9 / 9783319739069
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 19,2 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich