000 04454nam a22006015i 4500
001 978-0-387-74676-0
003 DE-He213
005 20161121231208.0
007 cr nn 008mamaa
008 100301s2008 xxu| s |||| 0|eng d
020 _a9780387746760
_9978-0-387-74676-0
024 7 _a10.1007/978-0-387-74676-0
_2doi
050 4 _aT57-57.97
072 7 _aPBW
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aDrew, John H.
_eauthor.
245 1 0 _aComputational Probability
_h[electronic resource] :
_bAlgorithms and Applications in the Mathematical Sciences /
_cby John H. Drew, Diane L. Evans, Andrew G. Glen, Lawrence M. Leemis.
264 1 _aBoston, MA :
_bSpringer US,
_c2008.
300 _aX, 222 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIn Operations Research & Management Science,
_x0884-8289 ;
_v117
505 0 _aComputational Probability -- Maple for APPL -- Algorithms for Continuous Random Variables -- Data Structures and Simple Algorithms -- Transformations of Random Variables -- Products of Random Variables -- Algorithms for Discrete Random Variables -- Data Structures and Simple Algorithms -- Sums of Independent Random Variables -- Order Statistics -- Applications -- Reliability and Survival Analysis -- Stochastic Simulation -- Other Applications.
520 _aComputational probability encompasses data structures and algorithms that have emerged over the past decade that allow researchers and students to focus on a new class of stochastic problems. COMPUTATIONAL PROBABILITY is the first book that examines and presents these computational methods in a systematic manner. The techniques described here address problems that require exact probability calculations, many of which have been considered intractable in the past. The first chapter introduces computational probability analysis, followed by a chapter on the Maple computer algebra system. The third chapter begins the description of APPL, the probability modeling language created by the authors. The book ends with three applications-based chapters that emphasize applications in survival analysis and stochastic simulation. The algorithmic material associated with continuous random variables is presented separately from the material for discrete random variables. Four sample algorithms, which are implemented in APPL, are presented in detail: transformations of continuous random variables, products of independent continuous random variables, sums of independent discrete random variables, and order statistics drawn from discrete populations. The APPL computational modeling language gives the field of probability a strong software resource to use for non-trivial problems and is available at no cost from the authors. APPL is currently being used in applications as wide-ranging as electric power revenue forecasting, analyzing cortical spike trains, and studying the supersonic expansion of hydrogen molecules. Requests for the software have come from fields as diverse as market research, pathology, neurophysiology, statistics, engineering, psychology, physics, medicine, and chemistry.
650 0 _aMathematics.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 0 _aComputer mathematics.
650 0 _aProbabilities.
650 0 _aStatistics.
650 1 4 _aMathematics.
650 2 4 _aApplications of Mathematics.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aComputational Mathematics and Numerical Analysis.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
700 1 _aEvans, Diane L.
_eauthor.
700 1 _aGlen, Andrew G.
_eauthor.
700 1 _aLeemis, Lawrence M.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387746753
830 0 _aIn Operations Research & Management Science,
_x0884-8289 ;
_v117
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-74676-0
912 _aZDB-2-SMA
950 _aMathematics and Statistics (Springer-11649)
999 _c509956
_d509956