New Statistical Developments in Data Science SIS 2017, Florence, Italy, June 28-30 /
This volume collects the extended versions of papers presented at the SIS Conference "Statistics and Data Science: new challenges, new generations", held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2019.
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| Έκδοση: | 1st ed. 2019. |
| Σειρά: | Springer Proceedings in Mathematics & Statistics,
288 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- PART I - Complex data analytics: A. Balzanella et al., Monitoring the spatial correlation among functional data streams through Moran's Index
- O. Banouar and S. Raghay, User query enrichment for personalized access to data through ontologies using matrix completion method
- C. Drago, Clustering Communities using Interval K-Means
- F. Murtagh, Text Mining and Big Textual Data: Relevant Statistical Models
- G. Ragozini et al., A three-way data analysis approach for analyzing multiplex networks
- M. Ruggieri et al., Comparing FPCA based on conditional quantile functions and FPCA based on conditional mean function
- F. Santelli et al., Statistical archetypal analysis for cognitive categorization
- A. Vanacore and M. S. Pellegrino, Inferring rater agreement with ordinal classification
- PART II - Knowledge based methods: J. Koskinen et al., Bayesian analysis of ERG models for multilevel, multiplex, and multilayered networks with sampled or missing data
- C. Scricciolo, Bayesian Kantorovich Deconvolution in Finite Mixture Models
- A. Sottosanti et al., Discovering and Locating High-Energy Extra-Galactic\Sources by Bayesian Mixture Modelling
- F. Stefanini and G. Callegaro, Bayesian estimation of causal effects in carcinogenicity tests based upon CTA
- M. Subbiah et al., Performance Comparison of Heterogeneity Measures for count data models in Bayesian Perspective
- PART III - Sampling techniques for Big Data exploration: M. S. Andreano et al., Sampling and modelling issues using Big Data in now-casting
- M. D'Alò et al., Sample design for the integration of population census and social surveys
- C. De Vitiis et al., Sampling schemes using scanner data for the consumer price index
- S. Polettini and S. Arima, An investigation of Hierarchical and Empirical Bayesian small area predictors under measurement error
- E. Rocco, Indicators for monitoring the survey data quality when non-response or a convenience sample occurs
- PART IV - Data Science methods for social and population studies: P. Balduzzi et al., The propensity to leave the country of origin of young Europeans
- F. Bassi et al., New Insights on Student Evaluation of Teaching in Italy
- A. Bikauskaite and D. Buono, Eurostat methodological network: Skills mapping for a collaborative statistical office
- M. Costa, The evaluation of the inequality between population subgroups
- M. Manisera et al., Basketball analytics using spatial tracking data
- I. Morlini and M. Scorza, New fuzzy composite indicators for dyslexia
- A. Righi et al., Who tweets in Italian? Demographic characteristics of Twitter users
- PART V - Applying Data Science in economics and labour market: A. Agapitov et al., An approach to developing a scoring system for peer-to-peer (p2p) lending platform
- P. Mariani et al., What do employers look for when hiring new graduates? Answers from the Electus survey
- A. Mazza and A. Punzo, Modeling Household Income with Contaminated Unimodal Distributions
- G. Punzo et al., Endowments and rewards in the labour market: their role in changing wage inequality in Europe
- V. Voytsekhovska and O. Butzbach, The approach towards the analysis of wage distribution equality dynamics in Poland based on linear dependences
- PART VI - Mathematical statistics for Data Science: R. Fontana and F. Rapallo, Unions of Orthogonal Arrays and their aberrations via Hilbert bases
- F. Lagona, A copula-based hidden Markov model for toroidal time Series
- A. Lanteri et al., A biased Kaczmarz algorithm for clustered equations
- A. Lepore, Nearly Unbiased Probability Plots for Extreme Value Distributions
- V. Mameli et al., Estimating High-Dimensional Regression Models with Bootstrap group Penalties.
