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Statistical Learning and Modeling in Data Analysis : Methods and Applications - Domenico Vistocco

Statistical Learning and Modeling in Data Analysis

Methods and Applications

By: Domenico Vistocco (Editor), Simona Balzano (Editor), Renato Salvatore (Editor), Maurizio Vichi (Editor), Giovanni C. Porzio (Editor)

Paperback | 14 July 2021

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Chapter 1 - Interpreting Effects in Generalized Linear Modeling (Alan Agresti, Claudia Tarantola, and Roberta Varriale)
Chapter 2 - ACE, AVAS and Robust Data Transformations: Performance of Investment Funds (Anthony C. Atkinson, Marco Riani, Aldo Corbellini, and Gianluca Morelli) Chapter 3 - Predictive Principal Component Analysis (Simona Balzano, Maja Bozic, Laura Marcis, and Renato Salvatore)
Chapter 4 - Robust model-based learning to discover new wheat varieties and discriminate adulterated kernels in X-ray images (Andrea Cappozzo, Francesca Greselin, and Thomas Brendan Murphy)
Chapter 5 - A dynamic model for ordinal time series: an application to consumers' perceptions of inflation (Marcella Corduas) Chapter 6 - Deep learning to jointly analyze images and clinical data for disease detection (Federica Crobu and Agostino Di Ciaccio)
Chapter 7 -Studying Affiliation Networks through Cluster CA and Blockmodeling (Daniela D'Ambrosio, Marco Serino, and Giancarlo Ragozini)
Chapter 8 - Sectioning Procedure on Geostatistical Indices Series of Pavement Road Profiles (Mauro D'Apuzzo, Rose-Line Spacagna, Azzurra Evangelisti, Daniela Santilli, and Vittorio Nicolosi)
Chapter 9 - Directional supervised learning through depth functions: an application to ECG waves analysis (Houyem Demni) Chapter 10 - Penalized vs. contrained approaches for clusterwise linear regression modelling (Roberto Di Mari, Stefano Antonio Gattone, and Roberto Rocci)
Chapter 11 - Effect measures for group comparisons in a two-component mixture model: a cyber risk analysis (Maria Iannario and Claudia Tarantola)
Chapter 12 - A Cramer-von Mises test of uniformity on the hypersphere (Eduardo Garcia-Portugues, Paula Navarro-Esteban, and Juan Antonio Cuesta-Albertos)
Chapter 13 - On mean and/or variance mixtures of normal distributions (Sharon X. Lee and Geoffrey J. McLachlan)
Chapter 14 - Robust depth-based inference in elliptical models (Stanislav Nagy and Jiři Dvořak)
Chapter 15 - Latent class analysis for the derivation of marketing decisions: An empirical study for BEV battery manufacturers (Friederike Paetz)
Chapter 16 - Small Area Estimation Diagnostics: the Case of the Fay-Herriot Model (Maria Chiara Pagliarella)
Chapter 17 - A comparison between methods to cluster mixed-type data: Gaussian mixtures versus Gower distance (Monia Ranalli and Roberto Rocci)
Chapter 18 - Exploring the gender gap in Erasmus student mobility flows (Marialuisa Restaino, Ilaria Primerano, and Maria Prosperina Vitale).

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