Beyond Traditional Probabilistic Methods in Economics: 809 - Rilegato

Rilegato

ISBN 10: 3030041999 ISBN 13: 9783030041991

Casa editrice: Springer-Nature New York Inc, 2018

Riassunto

<p>This book presents recent research on probabilistic methods in economics, from machine learning to statistical analysis. Economics is a very important – and at the same a very difficult discipline. It is not easy to predict how an economy will evolve or to identify the measures needed to make an economy prosper. One of the main reasons for this is the high level of uncertainty: different difficult-to-predict events can influence the future economic behavior. To make good predictions and reasonable recommendations, this uncertainty has to be taken into account.</p><p>In the past, most related research results were based on using traditional techniques from probability and statistics, such as p-value-based hypothesis testing. These techniques led to numerous successful applications, but in the last decades, several examples have emerged showing that these techniques often lead to unreliable and inaccurate predictions. It is therefore necessary to come up with new techniques for processing the corresponding uncertainty that go beyond the traditional probabilistic techniques.</p>This book focuses on such techniques, their economic applications and the remaining challenges, presenting both related theoretical developments and their practical applications.

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Dalla quarta di copertina

This book presents recent research on probabilistic methods in economics, from machine learning to statistical analysis. Economics is a very important – and at the same a very difficult discipline. It is not easy to predict how an economy will evolve or to identify the measures needed to make an economy prosper. One of the main reasons for this is the high level of uncertainty: different difficult-to-predict events can influence the future economic behavior. To make good predictions and reasonable recommendations, this uncertainty has to be taken into account.

In the past, most related research results were based on using traditional techniques from probability and statistics, such as p-value-based hypothesis testing. These techniques led to numerous successful applications, but in the last decades, several examples have emerged showing that these techniques often lead to unreliable and inaccurate predictions. It is therefore necessary to come up with new techniques for processing the corresponding uncertainty that go beyond the traditional probabilistic techniques.

This book focuses on such techniques, their economic applications and the remaining challenges, presenting both related theoretical developments and their practical applications.

Dettagli dell'edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 3030041999
• ISBN 13: 9783030041991
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 1157
• Redattore: Kreinovich Vladik, Thach Nguyen Ngoc, Trung Nguyen Duc, Van Thanh Dang
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Germania