000 | 02928nam a22004575i 4500 | ||
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001 | 978-3-540-26990-8 | ||
003 | DE-He213 | ||
005 | 20161121230932.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2005 gw | s |||| 0|eng d | ||
020 |
_a9783540269908 _9978-3-540-26990-8 |
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024 | 7 |
_a10.1007/b138428 _2doi |
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050 | 4 | _aQA273.A1-274.9 | |
050 | 4 | _aQA274-274.9 | |
072 | 7 |
_aPBT _2bicssc |
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072 | 7 |
_aPBWL _2bicssc |
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072 | 7 |
_aMAT029000 _2bisacsh |
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082 | 0 | 4 |
_a519.2 _223 |
100 | 1 |
_aStroock, Daniel W. _eauthor. |
|
245 | 1 | 3 |
_aAn Introduction to Markov Processes _h[electronic resource] / _cby Daniel W. Stroock. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2005. |
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300 |
_aXIV, 178 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aGraduate Texts in Mathematics, _x0072-5285 ; _v230 |
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505 | 0 | _aRandom Walks A Good Place to Begin -- Doeblin's Theory for Markov Chains -- More about the Ergodic Theory of Markov Chains -- Markov Processes in Continuous Time -- Reversible Markov Processes -- Some Mild Measure Theory. | |
520 | _aTo some extent, it would be accurate to summarize the contents of this book as an intolerably protracted description of what happens when either one raises a transition probability matrix P (i. e. , all entries (P)»j are n- negative and each row of P sums to 1) to higher and higher powers or one exponentiates R(P — I), where R is a diagonal matrix with non-negative entries. Indeed, when it comes right down to it, that is all that is done in this book. However, I, and others of my ilk, would take offense at such a dismissive characterization of the theory of Markov chains and processes with values in a countable state space, and a primary goal of mine in writing this book was to convince its readers that our offense would be warranted. The reason why I, and others of my persuasion, refuse to consider the theory here as no more than a subset of matrix theory is that to do so is to ignore the pervasive role that probability plays throughout. Namely, probability theory provides a model which both motivates and provides a context for what we are doing with these matrices. To wit, even the term "transition probability matrix" lends meaning to an otherwise rather peculiar set of hypotheses to make about a matrix. | ||
650 | 0 | _aMathematics. | |
650 | 0 | _aProbabilities. | |
650 | 1 | 4 | _aMathematics. |
650 | 2 | 4 | _aProbability Theory and Stochastic Processes. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540234999 |
830 | 0 |
_aGraduate Texts in Mathematics, _x0072-5285 ; _v230 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/b138428 |
912 | _aZDB-2-SMA | ||
950 | _aMathematics and Statistics (Springer-11649) | ||
999 |
_c506129 _d506129 |