大葉大學圖書館 |

A first course in probability and Markov chains[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	519.2/33
書名/作者:	A first course in probability and Markov chains/ Giuseppe Modica and Laura Poggiolini.
作者:	Modica, Giuseppe.
其他作者:	Poggiolini, Laura.
出版者:	Chichester, West Sussex : : John Wiley & Sons Ltd.,, 2013.
面頁冊數:	1 online resource (xii, 334 p.)
標題:	Markov processes.
ISBN:	9781118477793 (electronic bk.)
ISBN:	1118477790 (electronic bk.)
ISBN:	9781118477809 (electronic bk.)
ISBN:	1118477804 (electronic bk.)
ISBN:	9781118477748 (electronic bk.)
ISBN:	111847774X (electronic bk.)
書目註:	Includes bibliographical references and index.
摘要、提要註:	"Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra"--
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9781118477793

A first course in probability and Markov chains[electronic resource] /
Modica, Giuseppe.

A first course in probability and Markov chains[electronic resource] /Giuseppe Modica and Laura Poggiolini. - Chichester, West Sussex :John Wiley & Sons Ltd.,2013. - 1 online resource (xii, 334 p.)

Includes bibliographical references and index.

"Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra"--

ISBN: 9781118477793 (electronic bk.)

LCCN: 2012042679Subjects--Topical Terms:

369778
Markov processes.
Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: QA274.7 / .M63 2013

Dewey Class. No.: 519.2/33

A first course in probability and Markov chains[electronic resource] /
LDR:03463cam a2200409 i 4500 001 416358
003 OCoLC
005 20141203030517.0
006 m o d
007 cr |n||||||||a
008 150205s2013 enk ob 001 0 eng
010 $a 2012042679
020 $a 9781118477793 (electronic bk.)
020 $a 1118477790 (electronic bk.)
020 $a 9781118477809 (electronic bk.)
020 $a 1118477804 (electronic bk.)
020 $a 9781118477748 (electronic bk.)
020 $a 111847774X (electronic bk.)
020 $z 9781118477816
020 $z 1118477812
020 $z 9781299188280
020 $z 1299188281
020 $z 9781119944874 (hardback)
020 $z 1119944872 (hardback)
035 $a (OCoLC)813568123 $z (OCoLC)859157030
035 $a ocn813568123
040 $a DLC $b eng $c DLC $d YDX $d OCLCO $d DG1 $d N $d YDXCP $d N $d E7B $d OCLCQ $d UBY $d COO $d NOC $d OCLCO $d UMI $d DEBSZ $d TEFOD $d OCLCF
042 $a pcc
050 1 4 $a QA274.7 $b .M63 2013
082 0 0 $a 519.2/33 $2 23
100 1 $a Modica, Giuseppe. $3 465763
245 1 2 $a A first course in probability and Markov chains $h [electronic resource] / $c Giuseppe Modica and Laura Poggiolini.
260 $a Chichester, West Sussex : $b John Wiley & Sons Ltd., $c 2013.
300 $a 1 online resource (xii, 334 p.)
504 $a Includes bibliographical references and index.
520 $a "Provides an introduction to basic structures of probability with a view towards applications in information technology A First Course in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores notions and structures in probability, including combinatorics, probability measures, probability distributions, conditional probability, inclusion-exclusion formulas, random variables, dispersion indexes, independent random variables as well as weak and strong laws of large numbers and central limit theorem. In the second part of the book, focus is given to Discrete Time Discrete Markov Chains which is addressed together with an introduction to Poisson processes and Continuous Time Discrete Markov Chains. This book also looks at making use of measure theory notations that unify all the presentation, in particular avoiding the separate treatment of continuous and discrete distributions. A First Course in Probability and Markov Chains: Presents the basic elements of probability. Explores elementary probability with combinatorics, uniform probability, the inclusion-exclusion principle, independence and convergence of random variables. Features applications of Law of Large Numbers. Introduces Bernoulli and Poisson processes as well as discrete and continuous time Markov Chains with discrete states. Includes illustrations and examples throughout, along with solutions to problems featured in this book. The authors present a unified and comprehensive overview of probability and Markov Chains aimed at educating engineers working with probability and statistics as well as advanced undergraduate students in sciences and engineering with a basic background in mathematical analysis and linear algebra"-- $c Provided by publisher.
520 $a "A first course in Probability and Markov Chains presents an introduction to the basic elements in statistics and focuses in two main areas"-- $c Provided by publisher.
588 $a Description based on online resource; title from digital title page (viewed February 11, 2013).
650 0 $a Markov processes. $3 369778
655 4 $a Electronic books. $2 local $3 336502
700 1 $a Poggiolini, Laura. $3 588375
856 4 0 $u http://onlinelibrary.wiley.com/book/10.1002/9781118477793