國立高雄大學圖資館 |

Language: English

Back

Markov renewal and piecewise determi...

Cocozza-Thivent, Christiane.

Markov renewal and piecewise deterministic processes

Record Type:	Electronic resources : Monograph/item
Title/Author:	Markov renewal and piecewise deterministic processesby Christiane Cocozza-Thivent.
Author:	Cocozza-Thivent, Christiane.
Published:	Cham :Springer International Publishing :2021.
Description:	xiv, 252 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Markov processes.
Online resource:	https://doi.org/10.1007/978-3-030-70447-6
ISBN:	9783030704476$q(electronic bk.)

Markov renewal and piecewise deterministic processes
Cocozza-Thivent, Christiane.

Markov renewal and piecewise deterministic processes[electronic resource] /by Christiane Cocozza-Thivent. - Cham :Springer International Publishing :2021. - xiv, 252 p. :ill. (some col.), digital ;24 cm. - Probability theory and stochastic modelling,v.1002199-3130 ;. - Probability theory and stochastic modelling ;v.70..

Tools -- Markov renewal processes and related processes -- First steps with PDMP -- Hitting time distribution -- Intensity of some marked point pocesses -- Generalized Kolmogorov equations -- A martingale approach -- Stability -- Numerical methods -- Switching Processes -- Tools -- Interarrival distribution with several Dirac measures -- Algorithm convergence's proof.

This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Deterministic Markov Processes (PDMPs) A PDMP models a deterministic mechanism modified by jumps that occur at random times. The fields of applications are numerous : insurance and risk, biology, communication networks, dependability, supply management, etc. Indeed, the PDMPs studied so far are in fact deterministic functions of CSMPs (Completed Semi-Markov Processes), i.e. semi-Markov processes completed to become Markov processes. This remark leads to considerably broaden the definition of PDMPs and allows their properties to be deduced from those of CSMPs, which are easier to grasp. Stability is studied within a very general framework. In the other chapters, the results become more accurate as the assumptions become more precise. Generalized Chapman-Kolmogorov equations lead to numerical schemes. The last chapter is an opening on processes for which the deterministic flow of the PDMP is replaced with a Markov process. Marked point processes play a key role throughout this book.

ISBN: 9783030704476$q(electronic bk.)

Standard No.: 10.1007/978-3-030-70447-6doiSubjects--Topical Terms:

181910
Markov processes.

LC Class. No.: QA274.7 / .C636 2021

Dewey Class. No.: 519.233

Markov renewal and piecewise deterministic processes
LDR:02566nmm a2200337 a 4500 001 602492
003 DE-He213
005 20210707131718.0
006 m d
007 cr nn 008maaau
008 211112s2021 sz s 0 eng d
020 $a 9783030704476$q(electronic bk.)
020 $a 9783030704469$q(paper)
024 7 $a 10.1007/978-3-030-70447-6 $2 doi
035 $a 978-3-030-70447-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA274.7 $b .C636 2021
072 7 $a PBWL $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBWL $2 thema
082 0 4 $a 519.233 $2 23
090 $a QA274.7 $b .C667 2021
100 1 $a Cocozza-Thivent, Christiane. $3 898202
245 1 0 $a Markov renewal and piecewise deterministic processes $h [electronic resource] / $c by Christiane Cocozza-Thivent.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xiv, 252 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Probability theory and stochastic modelling, $x 2199-3130 ; $v v.100
505 0 $a Tools -- Markov renewal processes and related processes -- First steps with PDMP -- Hitting time distribution -- Intensity of some marked point pocesses -- Generalized Kolmogorov equations -- A martingale approach -- Stability -- Numerical methods -- Switching Processes -- Tools -- Interarrival distribution with several Dirac measures -- Algorithm convergence's proof.
520 $a This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Deterministic Markov Processes (PDMPs) A PDMP models a deterministic mechanism modified by jumps that occur at random times. The fields of applications are numerous : insurance and risk, biology, communication networks, dependability, supply management, etc. Indeed, the PDMPs studied so far are in fact deterministic functions of CSMPs (Completed Semi-Markov Processes), i.e. semi-Markov processes completed to become Markov processes. This remark leads to considerably broaden the definition of PDMPs and allows their properties to be deduced from those of CSMPs, which are easier to grasp. Stability is studied within a very general framework. In the other chapters, the results become more accurate as the assumptions become more precise. Generalized Chapman-Kolmogorov equations lead to numerical schemes. The last chapter is an opening on processes for which the deterministic flow of the PDMP is replaced with a Markov process. Marked point processes play a key role throughout this book.
650 0 $a Markov processes. $3 181910
650 1 4 $a Markov model. $3 841932
650 2 4 $a Probability and Statistics in Computer Science. $3 274053
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Probability theory and stochastic modelling ; $v v.70. $3 683306
856 4 0 $u https://doi.org/10.1007/978-3-030-70447-6
950 $a Mathematics and Statistics (SpringerNature-11649)