國立高雄大學圖資館 |

登入

回首頁

Modern series methods in econometrics and statistics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modern series methods in econometrics and statisticsby Chaohua Dong, Jiti Gao.
作者:	Dong, Chaohua.
其他作者:	Gao, Jiti.
出版者:	Singapore :Springer Nature Singapore :2025.
面頁冊數:	xiii, 372 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Econometrics.
電子資源:	https://doi.org/10.1007/978-981-96-2822-3
ISBN:	9789819628223$q(electronic bk.)

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 ;v.48..

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$q(electronic bk.)

Standard No.: 10.1007/978-981-96-2822-3doiSubjects--Topical Terms:

182271
Econometrics.

LC Class. No.: HB139 / .D66 2025

Dewey Class. No.: 330.015195

Modern series methods in econometrics and statistics
LDR:02541nmm a2200337 a 4500 001 687057
003 DE-He213
005 20250422130208.0
006 m d
007 cr nn 008maaau
008 260309s2025 si s 0 eng d
020 $a 9789819628223$q(electronic bk.)
020 $a 9789819628216$q(paper)
024 7 $a 10.1007/978-981-96-2822-3 $2 doi
035 $a 978-981-96-2822-3
040 $a GP $c GP
041 0 $a eng
050 4 $a HB139 $b .D66 2025
072 7 $a KCH $2 bicssc
072 7 $a BUS021000 $2 bisacsh
072 7 $a KCH $2 thema
082 0 4 $a 330.015195 $2 23
090 $a HB139 $b .D682 2025
100 1 $a Dong, Chaohua. $3 1001534
245 1 0 $a Modern series methods in econometrics and statistics $h [electronic resource] / $c by Chaohua Dong, Jiti Gao.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a xiii, 372 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Advanced studies in theoretical and applied econometrics, $x 2214-7977 ; $v 45
505 0 $a Motivations -- Series methods -- Applications of series methods -- Mathematical foundations.
520 $a 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.
650 0 $a Econometrics. $3 182271
650 0 $a Statistics. $3 182057
650 0 $a Series. $3 378252
650 2 4 $a Quantitative Economics. $3 913171
650 2 4 $a Microeconomics. $3 182798
650 2 4 $a Macroeconomics and Monetary Economics. $3 913170
650 2 4 $a Statistics in Business, Management, Economics, Finance, Insurance. $3 913173
700 1 $a Gao, Jiti. $3 1001535
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Advanced studies in theoretical and applied econometrics ; $v v.48. $3 711749
856 4 0 $u https://doi.org/10.1007/978-981-96-2822-3
950 $a Economics and Finance (SpringerNature-41170)