LEADER 01485nam--2200433---450- 001 990003272490203316 005 20090916124217.0 010 $a978-3-465-03603-6 (ln) 010 $a978-3-465-03602-9 (kt) 035 $a000327249 035 $aUSA01000327249 035 $a(ALEPH)000327249USA01 035 $a000327249 100 $a20090616h2009----km-y0itay50------ba 101 $ager 102 $aDE 105 $a||||||||001yy 200 1 $aBriefwechsel$e1925-1975$fRudolf Bultmann, Martin Heidegger$gherausgegeben von Andreas Gro?mann und Christof Landmesser$gmit einem Geleitwort von Eberhard Jüngel 210 $aFrankfurt am Main ; Tübingen$cV. Klostermann ; M. Siebeck$d2009 215 $aXXV, 342 p., [1] ritr.$cill.$d21 cm 606 0 $aBultmann,$bRudolf$xLettere [a] Heidegger, Martin$2BNCF 676 $a230.044 700 1$aBULTMANN,$bRudolf$0120634 701 1$aHEIDEGGER,$bMartin$010351 702 1$aGROßMANN,$bAndreas 702 1$aLANDMESSER,$bChristof 702 1$aJÜNGEL,$bEberhard 801 0$aIT$bsalbc$gISBD 912 $a990003272490203316 951 $aII.2. 5169$b217118 L.M.$cII.2.$d00226208 951 $aII.2. 5169 a$b216249 L.M.$cII.2.$d00228349 959 $aBK 969 $aUMA 979 $aPAOLA$b90$c20090616$lUSA01$h1129 979 $aPAOLA$b90$c20090616$lUSA01$h1144 979 $aPAOLA$b90$c20090616$lUSA01$h1208 979 $aPAOLA$b90$c20090916$lUSA01$h1242 996 $aBriefwechsel$91118322 997 $aUNISA LEADER 01585nam 2200481Ka 450 001 9910695552003321 005 20070207112922.0 035 $a(CKB)5470000002371251 035 $a(OCoLC)82171966 035 $a(EXLCZ)995470000002371251 100 $a20070207d2000 ua 0 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBOREAS TE-9 PAR and leaf nitrogen data for NSA species$b[electronic resource] /$fQinglai Dang, Hank Margolis and Marie Coyea 210 1$aGreenbelt, Md. :$cNASA Goddard Space Flight Center,$d[2000] 215 $a1 volume $cdigital, PDF file 225 1 $aTechnical report series on the Boreal Ecosystem-Atmosphere Study (BOREAS) ;$v158 225 1 $aNASA/TM ;$v2000-209891, v. 158 300 $aTitle from title screen (viewed on Feb. 7, 2007). 300 $a"October 2000." 320 $aIncludes bibliographical references. 606 $aChemical composition$2nasat 606 $aEcology$2nasat 606 $aFoliage$2nasat 606 $aForests$2nasat 606 $aNitrogen$2nasat 615 7$aChemical composition. 615 7$aEcology. 615 7$aFoliage. 615 7$aForests. 615 7$aNitrogen. 700 $aDang$b Qinglai$01413603 701 $aMargolis$b Hank$01399198 701 $aCoyea$b Marie$01413604 712 02$aGoddard Space Flight Center. 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910695552003321 996 $aBOREAS TE-9 PAR and leaf nitrogen data for NSA species$93510351 997 $aUNINA LEADER 05293nam 22007572 450 001 9910783061403321 005 20160511153343.0 010 $a1-107-12030-6 010 $a1-280-15912-X 010 $a0-511-11865-1 010 $a0-511-01878-9 010 $a0-511-15665-0 010 $a0-511-32934-2 010 $a0-511-51064-0 010 $a0-511-04599-9 035 $a(CKB)1000000000005257 035 $a(EBL)201438 035 $a(OCoLC)437063058 035 $a(SSID)ssj0000203942 035 $a(PQKBManifestationID)11172925 035 $a(PQKBTitleCode)TC0000203942 035 $a(PQKBWorkID)10176537 035 $a(PQKB)11163769 035 $a(UkCbUP)CR9780511510649 035 $a(MiAaPQ)EBC201438 035 $a(Au-PeEL)EBL201438 035 $a(CaPaEBR)ebr10014615 035 $a(CaONFJC)MIL15912 035 $a(PPN)261345117 035 $a(EXLCZ)991000000000005257 100 $a20090312d2002|||| uy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModeling aggregate behavior and fluctuations in economics $estochastic views of interacting agents /$fMasanao Aoki$b[electronic resource] 210 1$aCambridge :$cCambridge University Press,$d2002. 215 $a1 online resource (xv, 263 pages) $cdigital, PDF file(s) 300 $aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). 311 $a0-521-60619-5 311 $a0-521-78126-4 320 $aIncludes bibliographical references (p. 245-252) and indexes. 327 $tOur Objectives and Approaches --$tPartial List of Applications --$tStates: Vectors of Fractions of Types and Partition Vectors --$tVectors of Fractions --$tPartition Vectors --$tJump Markov Processes --$tThe Master Equation --$tDecomposable Random Combinatorial Structures --$tSizes and Limit Behavior of Large Fractions --$tSetting Up Dynamic Models --$tTwo Kinds of State Vectors --$tEmpirical Distributions --$tExchangeable Random Sequences --$tPartition Exchangeability --$tTransition Rates --$tDetailed-Balance Conditions and Stationary Distributions --$tThe Master Equation --$tContinuous-Time Dynamics --$tPower-Series Expansion --$tAggregate Dynamics and Fokker-Planck Equation --$tDiscrete-Time Dynamics --$tIntroductory Simple and Simplified Models --$tA Two-Sector Model of Fluctuations --$tClosed Binary Choice Models --$tA Polya Distribution Model --$tOpen Binary Models --$tTwo Logistic Process Models --$tModel 1: The Aggregate Dynamics and Associated Fluctuations --$tModel 2: Nonlinear Exit Rate --$tA Nonstationary Polya Model --$tAn Example: A Deterministic Analysis of Nonlinear Effects May Mislead! --$tAggregate Dynamics and Fluctuations of Simple Models --$tDynamics of Binary Choice Models --$tDynamics for the Aggregate Variable --$tPotentials --$tCritical Points and Hazard Function --$tMultiplicity--An Aspect of Random Combinatorial Features --$tEvaluating Alternatives --$tRepresentation of Relative Merits of Alternatives --$tValue Functions --$tExtreme Distributions and Gibbs Distributions --$tType I: Extreme Distribution. 330 $aThis book has two components: stochastic dynamics and stochastic random combinatorial analysis. The first discusses evolving patterns of interactions of a large but finite number of agents of several types. Changes of agent types or their choices or decisions over time are formulated as jump Markov processes with suitably specified transition rates: optimisations by agents make these rates generally endogenous. Probabilistic equilibrium selection rules are also discussed, together with the distributions of relative sizes of the bases of attraction. As the number of agents approaches infinity, we recover deterministic macroeconomic relations of more conventional economic models. The second component analyses how agents form clusters of various sizes. This has applications for discussing sizes or shares of markets by various agents which involve some combinatorial analysis patterned after the population genetics literature. These are shown to be relevant to distributions of returns to assets, volatility of returns, and power laws. 517 3 $aModeling Aggregate Behavior & Fluctuations in Economics 606 $aDemand (Economic theory)$xMathematical models 606 $aSupply and demand$xMathematical models 606 $aConsumption (Economics)$xMathematical models 606 $aBusiness cycles$xMathematical models 606 $aStatics and dynamics (Social sciences)$xMathematical models 606 $aStochastic processes$xMathematical models 615 0$aDemand (Economic theory)$xMathematical models. 615 0$aSupply and demand$xMathematical models. 615 0$aConsumption (Economics)$xMathematical models. 615 0$aBusiness cycles$xMathematical models. 615 0$aStatics and dynamics (Social sciences)$xMathematical models. 615 0$aStochastic processes$xMathematical models. 676 $a338.5/212 700 $aAoki$b Masanao$054078 801 0$bUkCbUP 801 1$bUkCbUP 906 $aBOOK 912 $a9910783061403321 996 $aModeling aggregate behavior and fluctuations in economics$91130040 997 $aUNINA