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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.

Mathematical statistics. --- Sampling (Statistics). --- Statistics. --- Mathematical statistics --- Sampling (Statistics) --- Mathematics --- Social Sciences --- Physical Sciences & Mathematics --- Mathematical Statistics --- Statistics - General --- Statistics --- Data processing. --- Statistical Theory and Methods. --- Statistics and Computing/Statistics Programs. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Statistics .