Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

Vladik Kreinovich

ISBN 10: 3030456188 / ISBN 13: 9783030456184

Published by Springer International Publishing, Springer International Publishing Jun 2020, 2020

About this Item

Neuware -Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Processing uncertainty is essential, considering that computers ¿ which help us understand real-life processes and make better decisions based on that understanding ¿ get their information from measurements or from expert estimates, neither of which is ever 100% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques. Therefore, it is important to master both techniques for processing data. This book is highly recommended for researchers and students interested in the latest results and challenges in uncertainty, as well as practitioners who want to learn how to use the corresponding state-of-the-art techniques.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 280 pp. Englisch.

Seller Inventory # 9783030456184

Bibliographic Details

• Title: Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas
• Publisher: Springer International Publishing, Springer International Publishing Jun 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 3030456188
• ISBN 13: 9783030456184
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 21D millimeters 241 millimeters width by 160 millimeters height by 21 millimeters depth
• Weight: 588 grams

About this title

Synopsis

Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Processing uncertainty is essential, considering that computers – which help us understand real-life processes and make better decisions based on that understanding – get their information from measurements or from expert estimates, neither of which is ever 100% accurate. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques. Therefore, it is important to master both techniques for processing data. This book is highly recommended for researchers and students interested in the latest results and challenges in uncertainty, as well as practitioners who want to learn how to use the corresponding state-of-the-art techniques.