New Statistical Developments in Data Science

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 – DataScience 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.