Statistical Learning and Modeling in Data Analysis: Methods and ApplicationsSimona Balzano, Giovanni C. Porzio, Renato Salvatore, Domenico Vistocco, Maurizio Vichi Springer Nature, 13 lug 2021 - 182 pagine The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification. |
Sommario
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| 9 | |
On Predicting Principal Components Through Linear Mixed Models | 17 |
Robust ModelBased Learning to Discover New Wheat Varieties and Discriminate Adulterated Kernels in XRay Images | 29 |
An Application to Consumers Perceptions of Inflation | 37 |
Deep Learning to Jointly Analyze Images and Clinical Data for Disease Detection | 46 |
Studying Affiliation Networks Through Cluster CA and Blockmodeling | 57 |
Sectioning Procedure on Geostatistical Indices Series of Pavement Road Profiles | 69 |
A Cyber Risk Analysis | 96 |
A Cramérvon Mises Test of Uniformity on the Hypersphere | 107 |
On Mean Andor Variance Mixtures of Normal Distributions | 117 |
Robust DepthBased Inference in Elliptical Models | 128 |
An Empirical Study for BEV Battery Manufacturers | 139 |
The Case of the FayHerriot Model | 148 |
Gaussian Mixtures Versus Gower Distance | 163 |
Exploring the Gender Gap in Erasmus Student Mobility Flows | 173 |
An Application to ECG Waves Analysis | 78 |
Penalized Versus Constrained Approaches for Clusterwise Linear Regression Modeling | 89 |
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