[教程] SAS_STAT9.2 User’s Guide, Second Edition The MCMC Procedure

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Chapter 52 & \) w: g8 k/ L# U+ A) S7 {TheMCMCProcedure Contents Overview:MCMCProcedure ............................ 3478 PROCMCMCComparedwithOtherSASProcedures ............3479 ) n5 F( {, R" ~+ P3 EGettingStarted:MCMCProcedure .......................... 3479 4 [4 Y2 m1 X% QSimpleLinearRegression ...........................3480 TheBehrens-FisherProblem ..........................3488 Mixed-EffectsModel .............................3492 Syntax:MCMCProcedure .............................. 3495 PROCMCMCStatement ...........................3496 ARRAYStatement ...............................3508 8 B& Z) F# K5 A( O$ T5 w" }) d  p1 uBEGINCNST/ENDCNSTStatement .....................3509 ! y  ]7 U4 `. ]% R' |1 HBEGINNODATA/ENDNODATAStatements .................3511 , \4 Q0 {1 [- Z) E! yBYStatement .................................3511 + {4 U2 X; l. Y) G6 UMODELStatement ...............................3512 8 L: }  N3 G5 a0 ]) JPARMSStatement ...............................3515 % g$ i/ G: i3 qPRIOR/HYPERPRIORStatement .......................3516 ProgrammingStatements ...........................3516 * `; x0 w7 b! m' D+ pUDSStatement .................................3518 Details:MCMCProcedure .............................. 3522 5 o; q5 C9 y2 {9 XHowPROCMCMCWorks ..........................3522 - [- D: b2 D, K4 V# h) |8 JBlockingofParameters ............................3523 Samplers ....................................3524 - Y2 W- z, [6 A# w2 g# dTuningtheProposalDistribution .......................3525 ; j: |2 y" M0 R& y) PInitialValuesoftheMarkovChains ......................3528 AssignmentsofParameters ..........................3528 " t/ O1 \# u: ^9 H: n2 u. j2 uStandardDistributions .............................3530 . B5 B& U/ G; I- a3 u: X! f( x/ sSpecifyingaNewDistribution .........................3541 % d& k8 U3 C1 D6 g% r8 iUsingDensityFunctionsintheProgrammingStatements ...........3542 5 k: |& K# z( S3 CTruncationandCensoring ...........................3544 , _# x7 r3 G, k$ f% d0 cMultivariateDensityFunctions ........................3546 % y+ o- e+ [! [! b$ eSomeUsefulSASFunctions ..........................3549 MatrixFunctionsinPROCMCMC ......................3551 ModelingJointLikelihood ...........................3556 8 P4 V0 D! m5 X/ N( i! tRegeneratingDiagnosticsPlots ........................3557 ; _8 l4 T* v7 F. w0 ^PosteriorPredictiveDistribution ........................3560 HandlingofMissingData ...........................3565 FloatingPointErrorsandOverflows ......................3565 HandlingErrorMessages ...........................3568 ComputationalResources ...........................3570 ( C  ]% t1 V& D8 w/ Y: N6 N3 WDisplayedOutput ................................3571 ODSTableNames ...............................3575 ODSGraphics .................................3577 / ]# K% G' ]! x3 b9 D5 q3 r/ N0 i# CExamples:MCMCProcedure ............................ 3578 Example52.1:SimulatingSamplesFromaKnownDensity .........3578 Example52.2:Box-CoxTransformation ...................3583 Example52.3:GeneralizedLinearModels ..................3592 Example52.4:NonlinearPoissonRegressionModels ............3605 7 B; u& G$ H, I( K2 E) n$ mExample52.5:Random-EffectsModels ...................3614 Example52.6:ChangePointModels .....................3630 0 J/ _$ t1 r, y1 {Example52.7:ExponentialandWeibullSurvivalAnalysis ..........3634 6 |. B- A7 N* YExample52.8:CoxModels ..........................3647 Example52.9:NormalRegressionwithIntervalCensoring .........3664 Example52.10:ConstrainedAnalysis ....................3666 Example52.11:ImplementaNewSamplingAlgorithm ...........3672 & i& [( h& _4 M9 pExample52.12:UsingaTransformationtoImproveMixing .........3683 ; u. \$ x: p, }% w7 Q' M1 J0 PExample52.13:Gelman-RubinDiagnostics .................3693 References ...................................... 3700 - D* @% |( w: U, A5 z 游客，如果您要查看本帖隐藏内容请回复

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