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Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.

Statistical science --- Operational research. Game theory --- Mathematical statistics --- stochastische analyse --- informatietechnologie --- statistisch onderzoek --- Statistics --- Computer Science --- Smoothness of functions --- Nonconvex programming --- Least absolute deviations (Statistics) --- Linear models (Statistics) --- Mathematical statistics. --- Computer science. --- Statistical Theory and Methods. --- Probability and Statistics in Computer Science. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Informatics --- Science --- Statistical methods --- Statistique mathématique --- Modules, théorie des --- Programmation non convexe --- Modèles linéaires (Statistique) --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B --- Statistics . --- Statistical analysis --- Statistical data --- Econometrics --- 303.0 --- 304.0 --- 305.976 --- AA / International- internationaal --- 519.2 --- Smooth functions --- Functions --- Global optimization --- Non-convex programming --- Programming (Mathematics) --- Models, Linear (Statistics) --- Mathematical models --- Absolute deviations, Least (Statistics) --- Absolute values, Least (Statistics) --- Deviations, Least absolute (Statistics) --- LAD (Statistics) --- Least absolute values (Statistics) --- Values, Least absolute (Statistics) --- Least squares --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Algoritmen. Optimisatie --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- Multivariate analysis.

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"Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice"--

Mathematical statistics --- Big data --- Data sets, Large --- Large data sets --- Statistical methods --- Data sets --- Big data - Statistical methods - Handbooks, manuals, etc

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This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

Statistical science --- Mathematics --- Biomathematics. Biometry. Biostatistics --- Computer. Automation --- medische statistiek --- bio-informatica --- big data --- machine learning --- biostatistiek --- computers --- informatica --- statistiek --- biometrie --- wiskunde --- statistisch onderzoek