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Modern series methods in econometric...
~
Dong, Chaohua.
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Modern series methods in econometrics and statistics
Record Type:
Electronic resources : Monograph/item
Title/Author:
Modern series methods in econometrics and statistics/ by Chaohua Dong, Jiti Gao.
Author:
Dong, Chaohua.
other author:
Gao, Jiti.
Published:
Singapore :Springer Nature Singapore : : 2025.,
Description:
xiii, 372 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:
Motivations -- Series methods -- Applications of series methods -- Mathematical foundations.
Contained By:
Springer Nature eBook
Subject:
Econometrics. -
Online resource:
https://doi.org/10.1007/978-981-96-2822-3
ISBN:
9789819628223
Modern series methods in econometrics and statistics
Dong, Chaohua.
Modern series methods in econometrics and statistics
[electronic resource] /by Chaohua Dong, Jiti Gao. - Singapore :Springer Nature Singapore :2025. - xiii, 372 p. :ill. (chiefly color), digital ;24 cm. - Advanced studies in theoretical and applied econometrics,452214-7977 ;. - Advanced studies in theoretical and applied econometrics ;45..
Motivations -- Series methods -- Applications of series methods -- Mathematical foundations.
This book introduces modern series methods with a focus on applications in econometrics and statistics. It explores how new orthogonal series techniques can address challenges in model building and estimation, particularly for variables with unbounded support, nonparametric nonstationary data, and high-dimensional models. By extending traditional series methods, which are typically limited to variables with bounded supports, this book provides tools to tackle emerging problems in econometrics and statistics effectively. The book is organized into the following key parts. Part one provides the mathematical foundation for modern series methods, offering the theoretical background needed for their application. Part two introduces fundamental econometric concepts, including conditional expectations and regression models, within the context of modern series techniques. The last part, part four examines advanced topics, such as the connections between series methods and generalized functions, and compares series methods with kernel methods, highlighting their respective strengths and use cases. With a balanced mix of theory and practical insights, this book is ideal for researchers, practitioners, and students looking to deepen their understanding of series methods and their applications in econometrics, statistics, and related fields.
ISBN: 9789819628223
Standard No.: 10.1007/978-981-96-2822-3doiSubjects--Topical Terms:
542934
Econometrics.
LC Class. No.: HB139 / .D66 2025
Dewey Class. No.: 330.015195
Modern series methods in econometrics and statistics
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This book introduces modern series methods with a focus on applications in econometrics and statistics. It explores how new orthogonal series techniques can address challenges in model building and estimation, particularly for variables with unbounded support, nonparametric nonstationary data, and high-dimensional models. By extending traditional series methods, which are typically limited to variables with bounded supports, this book provides tools to tackle emerging problems in econometrics and statistics effectively. The book is organized into the following key parts. Part one provides the mathematical foundation for modern series methods, offering the theoretical background needed for their application. Part two introduces fundamental econometric concepts, including conditional expectations and regression models, within the context of modern series techniques. The last part, part four examines advanced topics, such as the connections between series methods and generalized functions, and compares series methods with kernel methods, highlighting their respective strengths and use cases. With a balanced mix of theory and practical insights, this book is ideal for researchers, practitioners, and students looking to deepen their understanding of series methods and their applications in econometrics, statistics, and related fields.
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Economics and Finance (SpringerNature-41170)
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EB HB139 .D66 2025
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