東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Stable convergence and stable limit ...

Hausler, Erich.

Linked to FindBook

Google Book

Amazon

博客來

Stable convergence and stable limit theorems

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Stable convergence and stable limit theorems/ by Erich Hausler, Harald Luschgy.
Author:	Hausler, Erich.
other author:	Luschgy, Harald.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	x, 228 p. :ill., digital ;24 cm.
[NT 15003449]:	Preface -- 1.Weak Convergence of Markov Kernels -- 2.Stable Convergence -- 3.Applications -- 4.Stability of Limit Theorems -- 5.Stable Martingale Central Limit Theorems -- 6.Stable Functional Martingale Central Limit Theorems -- 7.A Stable Limit Theorem with Exponential Rate -- 8.Autoregression of Order One -- 9.Branching Processes -- A. Appendix -- B. Appendix -- Bibliography.
Contained By:	Springer eBooks
Subject:	Limit theorems (Probability theory) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-18329-9
ISBN:	9783319183299 (electronic bk.)

Stable convergence and stable limit theorems
Hausler, Erich.

Stable convergence and stable limit theorems[electronic resource] /by Erich Hausler, Harald Luschgy. - Cham :Springer International Publishing :2015. - x, 228 p. :ill., digital ;24 cm. - Probability theory and stochastic modelling,v.742199-3130 ;. - Probability theory and stochastic modelling ;v.70..

Preface -- 1.Weak Convergence of Markov Kernels -- 2.Stable Convergence -- 3.Applications -- 4.Stability of Limit Theorems -- 5.Stable Martingale Central Limit Theorems -- 6.Stable Functional Martingale Central Limit Theorems -- 7.A Stable Limit Theorem with Exponential Rate -- 8.Autoregression of Order One -- 9.Branching Processes -- A. Appendix -- B. Appendix -- Bibliography.

The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics - such as the classical central limit theorem - which are usually formulated in terms of convergence in distribution. Originated by Alfred Renyi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level with a solid knowledge of measure theoretic probability.

ISBN: 9783319183299 (electronic bk.)

Standard No.: 10.1007/978-3-319-18329-9doiSubjects--Topical Terms:

646262
Limit theorems (Probability theory)

LC Class. No.: QA273.67 / .H38 2015

Dewey Class. No.: 519.2

Stable convergence and stable limit theorems
LDR:02513nam a2200337 a 4500 001 2007809
003 DE-He213
005 20160122104534.0
006 m d
007 cr nn 008maaau
008 160219s2015 gw s 0 eng d
020 $a 9783319183299 (electronic bk.)
020 $a 9783319183282 (paper)
024 7 $a 10.1007/978-3-319-18329-9 $2 doi
035 $a 978-3-319-18329-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA273.67 $b .H38 2015
072 7 $a PBT $2 bicssc
072 7 $a PBWL $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.2 $2 23
090 $a QA273.67 $b .H376 2015
100 1 $a Hausler, Erich. $3 2156834
245 1 0 $a Stable convergence and stable limit theorems $h [electronic resource] / $c by Erich Hausler, Harald Luschgy.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a x, 228 p. : $b ill., digital ; $c 24 cm.
490 1 $a Probability theory and stochastic modelling, $x 2199-3130 ; $v v.74
505 0 $a Preface -- 1.Weak Convergence of Markov Kernels -- 2.Stable Convergence -- 3.Applications -- 4.Stability of Limit Theorems -- 5.Stable Martingale Central Limit Theorems -- 6.Stable Functional Martingale Central Limit Theorems -- 7.A Stable Limit Theorem with Exponential Rate -- 8.Autoregression of Order One -- 9.Branching Processes -- A. Appendix -- B. Appendix -- Bibliography.
520 $a The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics - such as the classical central limit theorem - which are usually formulated in terms of convergence in distribution. Originated by Alfred Renyi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level with a solid knowledge of measure theoretic probability.
650 0 $a Limit theorems (Probability theory) $3 646262
650 0 $a Convergence. $3 589031
650 1 4 $a Mathematics. $3 515831
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
650 2 4 $a Statistical Theory and Methods. $3 891074
700 1 $a Luschgy, Harald. $3 1071425
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Probability theory and stochastic modelling ; $v v.70. $3 2072045
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-18329-9
950 $a Mathematics and Statistics (Springer-11649)