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LEADER: 03821nam a22004335a 4500
001 013839928-X
005 20131206201349.0
008 121227s2000 xxu| s ||0| 0|eng d
020 $a9781461205098
020 $a9781461205098
020 $a9781461267959
024 7 $a10.1007/978-1-4612-0509-8$2doi
035 $a(Springer)9781461205098
040 $aSpringer
050 4 $aQA276-280
072 7 $aPBT$2bicssc
072 7 $aMAT029000$2bisacsh
082 04 $a519.5$223
100 1 $aWhittle, Peter,$eauthor.
245 10 $aProbability via Expectation /$cby Peter Whittle.
250 $aFourth Edition.
264 1 $aNew York, NY :$bSpringer New York :$bImprint: Springer,$c2000.
300 $aXXI, 353 p.$bonline resource.
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $atext file$bPDF$2rda
490 1 $aSpringer Texts in Statistics,$x1431-875X
505 0 $aUncertainty, Intuition and Expectation -- Expectation -- Probability -- Some Basic Models -- Conditioning -- Applications of the Independence Concept -- The Two Basic Limit Theorems -- Continuous Random Variables and Their Transformations -- Markov Processes in Discrete Time -- Markov Processes in Continuous Time -- Action Optimisation: Dynamic Programming -- Optimal Resource Allocation -- Finance: Option Pricing and the Implied Martingale -- Second-Order Theory -- Consistency and Extension: The Finite-Dimensional Case -- Stochastic Convergence -- Martingales -- Extension: Examples of the Infinite-Dimensional Case -- Large-Deviation Theory -- Quantum Mechanics.
520 $aThis book has exerted a continuing appeal since publication of its original edition in 1970. It develops the theory of probability from axioms on the expectation functional rather than on probability measure, demonstrates that the standard theory unrolls more naturally and economically this way, and demonstrates that applications of real interest can be addressed almost immediately. Early analysts of games of chance found the question "What is the fair price for entering this game?" quite as natural as "What is the probability of winning it?" Modern probability virtually adopts the former view; present-day treatments of conditioning, weak convergence, generalised processes and, notably, quantum mechanics start explicitly from an expectation characterisation. A secondary aim of the original text was to introduce fresh examples and convincing applications, and that aim is continued in this edition, a general revision plus addition of Chapters 11, 12, 13, and 18. Chapter 11 gives an economical introduction to dynamic programming, applied in Chapter 12 to the allocation problems represented by portfolio selection and the multi-armed bandit. The investment theme is continued in Chapter 13 with a critical investigation of the concept of 'risk-free' trading and the associated Black-Sholes formula. Chapter 18 develops the basic ideas of large deviations, now a standard and invaluable component of theory and tool in applications. The book is seen as an introduction to probability for students with a basic mathematical facility, covering the standard material, but different in that it is unified by its theme and covers an unusual range of modern applications. For these latter reasons it is of interest to a wide class of readers; probabilists will find the alternative approach of interest, physicists ad engineers will find it
650 10 $aStatistics.
650 0 $aDistribution (Probability theory)
650 0 $aStatistics.
650 24 $aStatistics, general.
650 24 $aProbability Theory and Stochastic Processes.
776 08 $iPrinted edition:$z9781461267959
830 0 $aSpringer Texts in Statistics.
988 $a20131119
906 $0VEN