東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Beyond traditional probabilistic met...

Kreinovich, Vladik.

FindBook

Google Book

Amazon

博客來

Beyond traditional probabilistic methods in economics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Beyond traditional probabilistic methods in economics/ edited by Vladik Kreinovich ... [et al.].
其他作者:	Kreinovich, Vladik.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xiv, 1157 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Economics, Mathematical. -
電子資源:	https://doi.org/10.1007/978-3-030-04200-4
ISBN:	9783030042004

Beyond traditional probabilistic methods in economics
Beyond traditional probabilistic methods in economics[electronic resource] /edited by Vladik Kreinovich ... [et al.]. - Cham :Springer International Publishing :2019. - xiv, 1157 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8091860-949X ;. - Studies in computational intelligence ;v.809..

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.

ISBN: 9783030042004

Standard No.: 10.1007/978-3-030-04200-4doiSubjects--Topical Terms:

647770
Economics, Mathematical.

LC Class. No.: HB135 / .B49 2019

Dewey Class. No.: 330.015195

Beyond traditional probabilistic methods in economics
LDR:02324nmm a2200325 a 4500 001 2178010
003 DE-He213
005 20190617095310.0
006 m d
007 cr nn 008maaau
008 191122s2019 gw s 0 eng d
020 $a 9783030042004 $q (electronic bk.)
020 $a 9783030041991 $q (paper)
024 7 $a 10.1007/978-3-030-04200-4 $2 doi
035 $a 978-3-030-04200-4
040 $a GP $c GP
041 0 $a eng
050 4 $a HB135 $b .B49 2019
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 330.015195 $2 23
090 $a HB135 $b .B573 2019
245 0 0 $a Beyond traditional probabilistic methods in economics $h [electronic resource] / $c edited by Vladik Kreinovich ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xiv, 1157 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.809
520 $a 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.
650 0 $a Economics, Mathematical. $3 647770
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Economic Theory/Quantitative Economics/Mathematical Methods. $3 2162305
700 1 $a Kreinovich, Vladik. $3 1965595
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v.809. $3 3381757
856 4 0 $u https://doi.org/10.1007/978-3-030-04200-4
950 $a Intelligent Technologies and Robotics (Springer-42732)