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

Stochastic processes and long range ...

Samorodnitsky, Gennady.

Stochastic processes and long range dependence

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stochastic processes and long range dependenceby Gennady Samorodnitsky.
作者:	Samorodnitsky, Gennady.
出版者:	Cham :Springer International Publishing :2016.
面頁冊數:	xi, 415 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Stochastic processes.
電子資源:	http://dx.doi.org/10.1007/978-3-319-45575-4
ISBN:	9783319455754$q(electronic bk.)

Stochastic processes and long range dependence
Samorodnitsky, Gennady.

Stochastic processes and long range dependence[electronic resource] /by Gennady Samorodnitsky. - Cham :Springer International Publishing :2016. - xi, 415 p. :ill., digital ;24 cm. - Springer series in operations research and financial engineering,1431-8598. - Springer series in operations research and financial engineering..

Preface -- Stationary Processes -- Ergodic Theory of Stationary Processes -- Infinitely Divisible Processes -- Heavy Tails -- Hurst Phenomenon -- Second-order Theory -- Fractionally Integrated Processes -- Self-similar Processes -- Long Range Dependence as a Phase Transition -- Appendix.

This monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory) The text is organized around the probabilistic properties of stationary processes that are important for determining the presence or absence of long memory. The first few chapters serve as an overview of the general theory of stochastic processes which gives the reader sufficient background, language, and models for the subsequent discussion of long memory. The later chapters devoted to long memory begin with an introduction to the subject along with a brief history of its development, followed by a presentation of what is currently the best known approach, applicable to stationary processes with a finite second moment. The book concludes with a chapter devoted to the author's own, less standard, point of view of long memory as a phase transition, and even includes some novel results. Most of the material in the book has not previously been published in a single self-contained volume, and can be used for a one- or two-semester graduate topics course. It is complete with helpful exercises and an appendix which describes a number of notions and results belonging to the topics used frequently throughout the book, such as topological groups and an overview of the Karamata theorems on regularly varying functions.

ISBN: 9783319455754$q(electronic bk.)

Standard No.: 10.1007/978-3-319-45575-4doiSubjects--Topical Terms:

181874
Stochastic processes.

LC Class. No.: QA274

Dewey Class. No.: 519.23

Stochastic processes and long range dependence
LDR:02728nmm a2200337 a 4500 001 500032
003 DE-He213
005 20161110135656.0
006 m d
007 cr nn 008maaau
008 170621s2016 gw s 0 eng d
020 $a 9783319455754$q(electronic bk.)
020 $a 9783319455747$q(paper)
024 7 $a 10.1007/978-3-319-45575-4 $2 doi
035 $a 978-3-319-45575-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA274
072 7 $a PBT $2 bicssc
072 7 $a PBWL $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.23 $2 23
090 $a QA274 $b .S191 2016
100 1 $a Samorodnitsky, Gennady. $3 763197
245 1 0 $a Stochastic processes and long range dependence $h [electronic resource] / $c by Gennady Samorodnitsky.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xi, 415 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer series in operations research and financial engineering, $x 1431-8598
505 0 $a Preface -- Stationary Processes -- Ergodic Theory of Stationary Processes -- Infinitely Divisible Processes -- Heavy Tails -- Hurst Phenomenon -- Second-order Theory -- Fractionally Integrated Processes -- Self-similar Processes -- Long Range Dependence as a Phase Transition -- Appendix.
520 $a This monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory) The text is organized around the probabilistic properties of stationary processes that are important for determining the presence or absence of long memory. The first few chapters serve as an overview of the general theory of stochastic processes which gives the reader sufficient background, language, and models for the subsequent discussion of long memory. The later chapters devoted to long memory begin with an introduction to the subject along with a brief history of its development, followed by a presentation of what is currently the best known approach, applicable to stationary processes with a finite second moment. The book concludes with a chapter devoted to the author's own, less standard, point of view of long memory as a phase transition, and even includes some novel results. Most of the material in the book has not previously been published in a single self-contained volume, and can be used for a one- or two-semester graduate topics course. It is complete with helpful exercises and an appendix which describes a number of notions and results belonging to the topics used frequently throughout the book, such as topological groups and an overview of the Karamata theorems on regularly varying functions.
650 0 $a Stochastic processes. $3 181874
650 1 4 $a Mathematics. $3 184409
650 2 4 $a Probability Theory and Stochastic Processes. $3 274061
650 2 4 $a Measure and Integration. $3 273777
650 2 4 $a Dynamical Systems and Ergodic Theory. $3 273794
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer series in operations research and financial engineering. $3 567467
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-45575-4
950 $a Mathematics and Statistics (Springer-11649)