MARC Record from marc_columbia

LEADER: 03642cam a2200589Ii 4500
001 15090994
005 20220514232118.0
006 m o d
007 cr |||||||||||
008 130607t20132013flua ob 001 0 eng
035 $a(OCoLC)ocn847230844
035 $a(NNC)15090994
040 $aCUS$beng$erda$epn$cCUS$dCUS$dN$T$dYDXCP$dOCLCF$dCRCPR$dOCLCQ$dEBLCP$dDEBSZ$dOCLCQ$dNRC$dMERUC$dUAB$dOCLCQ$dBUF$dERL$dUUM$dU3W$dNLE$dUKMGB$dOCLCQ$dTKN$dYDX$dTYFRS$dLEAUB$dOCLCQ$dOCLCO
016 7 $a018587267$2Uk
019 $a852757240
020 $a9781466504172$q(electronic bk.)
020 $a146650417X$q(electronic bk.)
020 $z9781466504059$q(hardcover ;$qacid-free paper)
020 $z1466504056$q(hardcover ;$qacid-free paper)
035 $a(OCoLC)847230844$z(OCoLC)852757240
037 $aTANDF_260545$bIngram Content Group
050 4 $aQA298$b.D46 2013
072 7 $aMAT$x041000$2bisacsh
082 04 $a518/.282$223
049 $aZCUA
100 1 $aDel Moral, Pierre,$eauthor.
245 10 $aMean field simulation for Monte Carlo integration /$cPierre Del Moral.
264 1 $aBoca Raton :$bTaylor & Francis,$c[2013]
264 4 $c©2013
300 $a1 online resource (xlvii, 577 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aChapman & Hall/CRC Monographs on Statistics & Applied Probability
504 $aIncludes bibliographical references and index.
505 0 $aMonte Carlo & mean field models -- Theory & applications -- I. Feynman-Kac models -- Feynman-Kac models -- Four equivalent particle interpretations -- Continuous time Feynman-Kac models -- Nonlinear evolutions of intensity measures -- II. Application domains -- Particle absorption models -- Signal processing and control systems -- III. Theoretical aspects -- Mean field Feynman-Kac models -- A general class of mean field models -- Empirical processes -- Feynman-Kac semigroups -- Intensity measure semigroups -- Particle density profiles -- Genealogical tree models -- Particle normalizing constants -- Backward particle Markov models.
588 0 $aPrint version record.
520 $aIn the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko.
650 0 $aMonte Carlo method.
650 0 $aMean field theory.
650 2 $aMonte Carlo Method
650 6 $aMéthode de Monte-Carlo.
650 6 $aThéorie de champ moyen.
650 7 $aMATHEMATICS$xNumerical Analysis.$2bisacsh
650 7 $aMean field theory.$2fast$0(OCoLC)fst01013145
650 7 $aMonte Carlo method.$2fast$0(OCoLC)fst01025819
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$aDel Moral, Pierre.$tMean field simulation for Monte Carlo integration.$dBoca Raton : Taylor & Francis, 2013$z9781466504059$w(DLC) 2013007647$w(OCoLC)754730139
830 0 $aChapman & Hall/CRC Monographs on Statistics & Applied Probability.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15090994$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS