國立虎尾科技大學 |

Understanding Markov Chains = Examples and Applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Understanding Markov Chains/ by Nicolas Privault.
其他題名:	Examples and Applications /
作者:	Privault, Nicolas.
面頁冊數:	XVII, 372 p. 44 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Probabilities. -
電子資源:	https://doi.org/10.1007/978-981-13-0659-4
ISBN:	9789811306594

Understanding Markov Chains = Examples and Applications /
Privault, Nicolas.

Understanding Markov ChainsExamples and Applications /[electronic resource] :by Nicolas Privault. - 2nd ed. 2018. - XVII, 372 p. 44 illus.online resource. - Springer Undergraduate Mathematics Series,1615-2085. - Springer Undergraduate Mathematics Series,.

Probability Background -- Gambling Problems -- Random Walks -- Discrete-Time Markov Chains -- First Step Analysis -- Classification of States -- Long-Run Behavior of Markov Chains -- Branching Processes -- Continuous-Time Markov Chains -- Discrete-Time Martingales -- Spatial Poisson Processes -- Reliability Theory.

This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a particular focus on the first step analysis technique and its applications to average hitting times and ruin probabilities. It also discusses classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes. It first examines in detail two important examples (gambling processes and random walks) before presenting the general theory itself in the subsequent chapters. It also provides an introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times, together with a chapter on spatial Poisson processes. The concepts presented are illustrated by examples, 138 exercises and 9 problems with their solutions.

ISBN: 9789811306594

Standard No.: 10.1007/978-981-13-0659-4doiSubjects--Topical Terms:

527847
Probabilities.

LC Class. No.: QA273.A1-274.9

Dewey Class. No.: 519.2

Understanding Markov Chains = Examples and Applications /
LDR:02573nam a22004215i 4500 001 990021
003 DE-He213
005 20200703092134.0
007 cr nn 008mamaa
008 201225s2018 si | s |||| 0|eng d
020 $a 9789811306594 $9 978-981-13-0659-4
024 7 $a 10.1007/978-981-13-0659-4 $2 doi
035 $a 978-981-13-0659-4
050 4 $a QA273.A1-274.9
050 4 $a QA274-274.9
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a PBWL $2 thema
082 0 4 $a 519.2 $2 23
100 1 $a Privault, Nicolas. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 768970
245 1 0 $a Understanding Markov Chains $h [electronic resource] : $b Examples and Applications / $c by Nicolas Privault.
250 $a 2nd ed. 2018.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2018.
300 $a XVII, 372 p. 44 illus. $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
490 1 $a Springer Undergraduate Mathematics Series, $x 1615-2085
505 0 $a Probability Background -- Gambling Problems -- Random Walks -- Discrete-Time Markov Chains -- First Step Analysis -- Classification of States -- Long-Run Behavior of Markov Chains -- Branching Processes -- Continuous-Time Markov Chains -- Discrete-Time Martingales -- Spatial Poisson Processes -- Reliability Theory.
520 $a This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a particular focus on the first step analysis technique and its applications to average hitting times and ruin probabilities. It also discusses classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes. It first examines in detail two important examples (gambling processes and random walks) before presenting the general theory itself in the subsequent chapters. It also provides an introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times, together with a chapter on spatial Poisson processes. The concepts presented are illustrated by examples, 138 exercises and 9 problems with their solutions.
650 0 $a Probabilities. $3 527847
650 0 $a Statistics . $3 1253516
650 1 4 $a Probability Theory and Stochastic Processes. $3 593945
650 2 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811306587
776 0 8 $i Printed edition: $z 9789811306600
830 0 $a Springer Undergraduate Mathematics Series, $x 1615-2085 $3 1255356
856 4 0 $u https://doi.org/10.1007/978-981-13-0659-4
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)