Luis A. García-Escudero (ed.); Alfonso Gordaliza (ed.); Agustín Mayo (ed.); María Asunción Lubiano Gomez (ed.); Maria A Gil Springer (2022) Pehmeäkantinen kirja
Kimberly A. Gordon Biddle; Ana G. Garcia-Nevarez; Wanda J. Roundtree Henderson; Alicia Valero-Kerrick SAGE Publications Inc (2013) Pehmeäkantinen kirja
Gemma Fajardo-García; Antonio Fici; Hagen Henrÿ; David Hiez; Deolinda A. Meira; Hans-H. Muenker; Ian Snaith Intersentia Ltd (2017) Pehmeäkantinen kirja
Juan Luis Navarro Mesa; Alfonso Ortega; António Teixeira; Eduardo Hernández Pérez; Pedro Quintana Morales; A Ravelo Garcia Springer International Publishing AG (2014) Pehmeäkantinen kirja
Juan A. Botia; Juan Antonio Alvarez-Garcia; Kaori Fujinami; Paolo Barsocchi; Till Riedel Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2013) Pehmeäkantinen kirja
Nowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science.
This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness.