國立虎尾科技大學 |

The Elements of Hawkes Processes

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The Elements of Hawkes Processes/ by Patrick J. Laub, Young Lee, Thomas Taimre.
Author:	Laub, Patrick J.
other author:	Lee, Young.
Description:	XIV, 133 p. 121 illus., 119 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-3-030-84639-8
ISBN:	9783030846398

The Elements of Hawkes Processes
Laub, Patrick J.

The Elements of Hawkes Processes[electronic resource] /by Patrick J. Laub, Young Lee, Thomas Taimre. - 1st ed. 2021. - XIV, 133 p. 121 illus., 119 illus. in color.online resource.

Background -- Hawes Process Essentials -- Simulation Methods -- Likelihood Methods -- EM Algorithm -- Bayesian Methods -- Spectral Methods -- Goodness of Fit -- Traditional Applications -- Financial and Actuarial Applications -- Biological Applications.

Hawkes processes are studied and used in a wide range of disciplines: mathematics, social sciences, and earthquake modelling, to name a few. This book presents a selective coverage of the core and recent topics in the broad field of Hawkes processes. It consists of three parts. Parts I and II summarise and provide an overview of core theory (including key simulation methods) and inference methods, complemented by a selection of recent research developments and applications. Part III is devoted to case studies in seismology and finance that connect the core theory and inference methods to practical scenarios. This book is designed primarily for applied probabilists, statisticians, and machine learners. However, the mathematical prerequisites have been kept to a minimum so that the content will also be of interest to undergraduates in advanced mathematics and statistics, as well as machine learning practitioners. Knowledge of matrix theory with basics of probability theory, including Poisson processes, is considered a prerequisite. Colour-blind-friendly illustrations are included.

ISBN: 9783030846398

Standard No.: 10.1007/978-3-030-84639-8doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

The Elements of Hawkes Processes
LDR:02717nam a22003975i 4500 001 1059527
003 DE-He213
005 20220113192601.0
007 cr nn 008mamaa
008 220414s2021 sz | s |||| 0|eng d
020 $a 9783030846398 $9 978-3-030-84639-8
024 7 $a 10.1007/978-3-030-84639-8 $2 doi
035 $a 978-3-030-84639-8
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
100 1 $a Laub, Patrick J. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1366241
245 1 4 $a The Elements of Hawkes Processes $h [electronic resource] / $c by Patrick J. Laub, Young Lee, Thomas Taimre.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XIV, 133 p. 121 illus., 119 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Background -- Hawes Process Essentials -- Simulation Methods -- Likelihood Methods -- EM Algorithm -- Bayesian Methods -- Spectral Methods -- Goodness of Fit -- Traditional Applications -- Financial and Actuarial Applications -- Biological Applications.
520 $a Hawkes processes are studied and used in a wide range of disciplines: mathematics, social sciences, and earthquake modelling, to name a few. This book presents a selective coverage of the core and recent topics in the broad field of Hawkes processes. It consists of three parts. Parts I and II summarise and provide an overview of core theory (including key simulation methods) and inference methods, complemented by a selection of recent research developments and applications. Part III is devoted to case studies in seismology and finance that connect the core theory and inference methods to practical scenarios. This book is designed primarily for applied probabilists, statisticians, and machine learners. However, the mathematical prerequisites have been kept to a minimum so that the content will also be of interest to undergraduates in advanced mathematics and statistics, as well as machine learning practitioners. Knowledge of matrix theory with basics of probability theory, including Poisson processes, is considered a prerequisite. Colour-blind-friendly illustrations are included.
650 0 $a Statistics . $3 1253516
650 0 $a Probabilities. $3 527847
650 0 $a Machine learning. $3 561253
650 1 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Probability Theory. $3 1366244
650 2 4 $a Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 1366002
650 2 4 $a Machine Learning. $3 1137723
700 1 $a Lee, Young. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1366242
700 1 $a Taimre, Thomas. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1366243
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030846381
776 0 8 $i Printed edition: $z 9783030846404
776 0 8 $i Printed edition: $z 9783030846411
856 4 0 $u https://doi.org/10.1007/978-3-030-84639-8
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)