Atjaunināt sīkdatņu piekrišanu

E-grāmata: Stochastic Processes: An Introduction, Third Edition

4.00/5 (2 ratings by Goodreads)
(Keele University, Staffordshire, UK), (Keele University, Staffordshire, UK)
Citas grāmatas par šo tēmu:
  • Formāts - EPUB+DRM
  • Cena: 60,10 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
Stochastic Processes: An Introduction, Third EditionPalielināt
Citas grāmatas par šo tēmu:

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general population models, and present an extended discussion on the analysis of associated stationary processes in queues.

The book also explores reliability and other random processes, such as branching, martingales, and simple epidemics. A new chapter describing Brownian motion, where the outcomes are continuously observed over continuous time, is included. Further applications, worked examples and problems, and biographical details have been added to this edition. Much of the text has been reworked. The appendix contains key results in probability for reference.

This concise, updated book makes the material accessible, highlighting simple applications and examples. A solutions manual with fully worked answers of all end-of-chapter problems, and Mathematica® and R programs illustrating many processes discussed in the book, can be downloaded from crcpress.com.

Recenzijas

Praise for the second edition:

" a clear, easily understandable and rather short overview on stochastic processes. The different topics are motivated very well, there are many graphs and 50theoretical and practicalexamples. the book is written very carefully for beginners, one could not imagine a better book." Dominik Wied, Statistical Papers (2011) 52

" a good resource as a textbook or as a reference to complement other literature, especially with the examples and problems provided." Biometrics, 67, September 2011

Preface to the Third Edition xiii
1 Some Background on Probability
1(32)
1.1 Introduction
1(1)
1.2 Probability
1(4)
1.3 Conditional probability and independence
5(3)
1.4 Discrete random variables
8(1)
1.5 Continuous random variables
9(2)
1.6 Mean and variance
11(1)
1.7 Some standard discrete probability distributions
12(3)
1.8 Some standard continuous probability distributions
15(3)
1.9 Generating functions
18(5)
1.10 Conditional expectation
23(4)
1.11 Problems
27(6)
2 Some Gambling Problems
33(16)
2.1 Gambler's ruin
33(1)
2.2 Probability of ruin
33(4)
2.3 Some numerical simulations
37(2)
2.4 Duration of the game
39(2)
2.5 Some variations of gambler's ruin
41(3)
2.5.1 The infinitely rich opponent
41(2)
2.5.2 The generous opponent
43(1)
2.5.3 Changing the stakes
43(1)
2.6 Problems
44(5)
3 Random Walks
49(16)
3.1 Introduction
49(1)
3.2 Unrestricted random walks
50(2)
3.3 The exact probability distribution of a random walk
52(2)
3.4 First returns of the symmetric random walk
54(3)
3.5 Problems
57(8)
4 Markov Chains
65(40)
4.1 States and transitions
65(1)
4.2 Transition probabilities
66(4)
4.3 General two-state Markov chains
70(2)
4.4 Powers of the general transition matrix
72(8)
4.5 Gambler's ruin as a Markov chain
80(3)
4.6 Classification of states
83(7)
4.7 Classification of chains
90(4)
4.8 A wildlife Markov chain model
94(2)
4.9 Problems
96(9)
5 Poisson Processes
105(14)
5.1 Introduction
105(1)
5.2 The Poisson process
105(3)
5.3 Partition theorem approach
108(1)
5.4 Iterative method
109(1)
5.5 The generating function
110(2)
5.6 Arrival times
112(3)
5.7 Summary of the Poisson process
115(1)
5.8 Problems
115(4)
6 Birth and Death Processes
119(26)
6.1 Introduction
119(1)
6.2 The birth process
119(3)
6.3 Birth process: Generating function equation
122(2)
6.4 The death process
124(3)
6.5 The combined birth and death process
127(5)
6.6 General population processes
132(3)
6.7 Problems
135(10)
7 Queues
145(24)
7.1 Introduction
145(1)
7.2 The single-server queue
146(2)
7.3 The limiting process
148(6)
7.4 Queues with multiple servers
154(5)
7.5 Queues with fixed service times
159(3)
7.6 Classification of queues
162(1)
7.7 Problems
162(7)
8 Reliability and Renewal
169(14)
8.1 Introduction
169(1)
8.2 The reliability function
169(2)
8.3 Exponential distribution and reliability
171(1)
8.4 Mean time to failure
172(1)
8.5 Reliability of series and parallel systems
173(3)
8.6 Renewal processes
176(2)
8.7 Expected number of renewals
178(1)
8.8 Problems
179(4)
9 Branching and Other Random Processes
183(30)
9.1 Introduction
183(1)
9.2 Generational growth
183(3)
9.3 Mean and variance
186(2)
9.4 Probability of extinction
188(3)
9.5 Branching processes and martingales
191(4)
9.6 Stopping rules
195(2)
9.7 A continuous time epidemic
197(2)
9.8 A discrete time epidemic model
199(3)
9.9 Deterministic epidemic models
202(2)
9.10 An iterative solution scheme for the simple epidemic
204(3)
9.11 Problems
207(6)
10 Brownian Motion: Wiener Process
213(14)
10.1 Introduction
213(1)
10.2 Brownian motion
213(2)
10.3 Wiener process as a limit of a random walk
215(2)
10.4 Brownian motion with drift
217(1)
10.5 Scaling
217(2)
10.6 First visit times
219(2)
10.7 Other Brownian motions in one dimension
221(2)
10.8 Brownian motion in more than one dimension
223(1)
10.9 Problems
224(3)
11 Computer Simulations and Projects
227(10)
Answers and Comments on End-of-Chapter Problems 237(8)
Appendix 245(4)
References and Further Reading 249(2)
Index 251
Peter W. Jones is a professor and Pro Vice Chancellor for Research and Enterprise at Keele University in Staffordshire, UK.

Peter Smith is a Professor Emeritus in the School of Computing and Mathematics at Keele University in Staffordshire, UK.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97814987792346e.html
Keywords: