國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Statistical estimation for truncated...

Akahira, Masafumi.

Statistical estimation for truncated exponential families

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical estimation for truncated exponential familiesby Masafumi Akahira.
作者:	Akahira, Masafumi.
出版者:	Singapore :Springer Singapore :2017.
面頁冊數:	xi, 122 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Estimation theory.
電子資源:	http://dx.doi.org/10.1007/978-981-10-5296-5
ISBN:	9789811052965$q(electronic bk.)

Statistical estimation for truncated exponential families
Akahira, Masafumi.

Statistical estimation for truncated exponential families[electronic resource] /by Masafumi Akahira. - Singapore :Springer Singapore :2017. - xi, 122 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

This book presents new findings on nonregular statistical estimation. Unlike other books on this topic, its major emphasis is on helping readers understand the meaning and implications of both regularity and irregularity through a certain family of distributions. In particular, it focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical nonregular family. This focus includes the (truncated) Pareto distribution, which is widely used in various fields such as finance, physics, hydrology, geology, astronomy, and other disciplines. The family is essential in that it links both regular and nonregular distributions, as it becomes a regular exponential family if the truncation parameter is known. The emphasis is on presenting new results on the maximum likelihood estimation of a natural parameter or truncation parameter if one of them is a nuisance parameter. In order to obtain more information on the truncation, the Bayesian approach is also considered. Further, the application to some useful truncated distributions is discussed. The illustrated clarification of the nonregular structure provides researchers and practitioners with a solid basis for further research and applications.

ISBN: 9789811052965$q(electronic bk.)

Standard No.: 10.1007/978-981-10-5296-5doiSubjects--Topical Terms:

181864
Estimation theory.

LC Class. No.: QA276.8

Dewey Class. No.: 519.544

Statistical estimation for truncated exponential families
LDR:02244nmm a2200313 a 4500 001 520401
003 DE-He213
005 20170727194110.0
006 m d
007 cr nn 008maaau
008 180425s2017 si s 0 eng d
020 $a 9789811052965$q(electronic bk.)
020 $a 9789811052958$q(paper)
024 7 $a 10.1007/978-981-10-5296-5 $2 doi
035 $a 978-981-10-5296-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.8
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.544 $2 23
090 $a QA276.8 $b .A313 2017
100 1 $a Akahira, Masafumi. $3 789680
245 1 0 $a Statistical estimation for truncated exponential families $h [electronic resource] / $c by Masafumi Akahira.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2017.
300 $a xi, 122 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics, $x 2191-544X
520 $a This book presents new findings on nonregular statistical estimation. Unlike other books on this topic, its major emphasis is on helping readers understand the meaning and implications of both regularity and irregularity through a certain family of distributions. In particular, it focuses on a truncated exponential family of distributions with a natural parameter and truncation parameter as a typical nonregular family. This focus includes the (truncated) Pareto distribution, which is widely used in various fields such as finance, physics, hydrology, geology, astronomy, and other disciplines. The family is essential in that it links both regular and nonregular distributions, as it becomes a regular exponential family if the truncation parameter is known. The emphasis is on presenting new results on the maximum likelihood estimation of a natural parameter or truncation parameter if one of them is a nuisance parameter. In order to obtain more information on the truncation, the Bayesian approach is also considered. Further, the application to some useful truncated distributions is discussed. The illustrated clarification of the nonregular structure provides researchers and practitioners with a solid basis for further research and applications.
650 0 $a Estimation theory. $3 181864
650 1 4 $a Statistics. $3 182057
650 2 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Statistics and Computing/Statistics Programs. $3 275710
650 2 4 $a Statistics for Business/Economics/Mathematical Finance/Insurance. $3 274062
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 348605
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in statistics. $3 557771
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-5296-5
950 $a Mathematics and Statistics (Springer-11649)