Information and Divergence Measures

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Tác giả: Alex Karagrigoriou, Andreas Makrides

Ngôn ngữ: eng

ISBN-13: 978-3036583860

ISBN-13: 978-3036583877

ISBN: books978-3-0365-8387-7

Ký hiệu phân loại:

Thông tin xuất bản: MDPI - Multidisciplinary Digital Publishing Institute 2023

Mô tả vật lý: 1 electronic resource (282 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 374082

The concept of distance is important for establishing the degree of similarity and/or closeness between functions, populations, or distributions. As a result, distances are related to inferential statistics, including problems related to both estimation and hypothesis testing, as well as modelling with applications in regression analysis, multivariate analysis, actuarial science, portfolio optimization, survival analysis, reliability theory, and many other areas. Thus, entropy and divergence measures are always a central concern for scientists, researchers, medical experts, engineers, industrial managers, computer experts, data analysts, and other professionals. This reprint focuses on recent developments in information and divergence measures and presents new theoretical issues as well as solutions to important practical problems and case studies illustrating the great applicability of these innovative techniques and methods. The contributions in this reprint highlight the diversity of topics in this scientific field.
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