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标题: [教程] SAS_STAT9.2 User’s Guide, Second Edition The MCMC Procedure [打印本页]
作者: 建不了的模。    时间: 2014-7-22 09:28
标题: [教程] SAS_STAT9.2 User’s Guide, Second Edition The MCMC Procedure

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Chapter 52
: D% G- V5 }- g3 X7 ITheMCMCProcedure" l7 ~" X# ?% j9 o1 k5 L
Contents/ Y+ h5 ]& k- E5 T6 I  R
Overview:MCMCProcedure ............................ 34785 Y0 D0 Y( k  W( O$ r
PROCMCMCComparedwithOtherSASProcedures ............3479
3 k8 s% E' m0 \2 L( oGettingStarted:MCMCProcedure .......................... 3479' D, M; m( T+ a7 s, X
SimpleLinearRegression ...........................3480
$ y, W6 ^7 W; g, [# ]+ WTheBehrens-FisherProblem ..........................3488
8 {8 s4 d% [/ I: e/ BMixed-EffectsModel .............................34927 f: T. K! e. S
Syntax:MCMCProcedure .............................. 3495: `* ^2 Q3 _+ h5 g5 l
PROCMCMCStatement ...........................3496
( H7 g* f( V* a' lARRAYStatement ...............................3508
' I* e( n& [7 p4 |9 W7 Y* dBEGINCNST/ENDCNSTStatement .....................3509, F; x! J. w* {9 Z/ l
BEGINNODATA/ENDNODATAStatements .................3511
" N8 E; F9 b: T- WBYStatement .................................3511
% U0 V5 C1 P  _' t+ I8 wMODELStatement ...............................3512
2 z9 E. F4 M, t, }( A# uPARMSStatement ...............................3515
) h2 c+ N* k; ]# _3 Q. N5 ?PRIOR/HYPERPRIORStatement .......................3516
; @4 {0 |' T- E1 N+ U: n" W& s/ {# k2 OProgrammingStatements ...........................3516
* W- R4 _- D! W  ?* YUDSStatement .................................3518# i3 ]# C( X2 N. }( l
Details:MCMCProcedure .............................. 3522
! G( M* A% ~; z( }HowPROCMCMCWorks ..........................3522
: v+ P2 R) F3 n" }( aBlockingofParameters ............................35236 D: y1 Z: V2 H/ U, i" x: n
Samplers ....................................35241 k1 A5 ^) u0 ?* n, f4 ^
TuningtheProposalDistribution .......................3525# W* G0 _" {0 Q1 d" H1 |  z# d8 N
InitialValuesoftheMarkovChains ......................3528
: y9 d0 I8 M1 E, Q" k4 b' x* `AssignmentsofParameters ..........................3528, ~6 H1 x/ g# `) y* t. U
StandardDistributions .............................3530
0 D7 K4 l4 ?5 j+ D. C- B- ISpecifyingaNewDistribution .........................3541
( l# y1 t! W5 H% V! B. L; `UsingDensityFunctionsintheProgrammingStatements ...........3542' {. [- f% ^% E! m! S
TruncationandCensoring ...........................3544
9 ^+ I/ w, i+ T, a( l% eMultivariateDensityFunctions ........................3546, \  ?3 s$ X9 N
SomeUsefulSASFunctions ..........................3549; A) i: i9 m. Q! R
MatrixFunctionsinPROCMCMC ......................3551: Z9 H" e; `. {& m* y( v
ModelingJointLikelihood ...........................3556
5 ~/ I- |9 w  G5 ?2 e0 U) }: KRegeneratingDiagnosticsPlots ........................3557( d) C# q0 G  ?$ S" v5 F
PosteriorPredictiveDistribution ........................3560( d- V, ?. |8 ^& {- I( c0 @  E2 p
HandlingofMissingData ...........................3565
- t$ O0 w" f; |" oFloatingPointErrorsandOverflows ......................35651 z) H) n  H2 j( }
HandlingErrorMessages ...........................35680 N2 M: m- r# S* E: \
ComputationalResources ...........................3570
7 E* x+ E' a  q7 H# D) Q- tDisplayedOutput ................................35715 E8 @7 T4 o7 g  j6 V
ODSTableNames ...............................3575
$ @/ X7 _) \3 b: U4 R! ]1 lODSGraphics .................................3577
9 `% G1 f% s. @1 c$ w5 UExamples:MCMCProcedure ............................ 3578
. F. a7 u: N5 t. ~Example52.1:SimulatingSamplesFromaKnownDensity .........3578
) T7 i4 E: j$ W7 `3 k9 w5 m) }: O" x0 oExample52.2:Box-CoxTransformation ...................3583
: i; _9 F; {& s* U8 f* FExample52.3:GeneralizedLinearModels ..................35927 D# Z0 b8 d3 t* k
Example52.4:NonlinearPoissonRegressionModels ............3605
8 S/ S3 c( _, T5 k/ O# BExample52.5:Random-EffectsModels ...................3614
7 T8 W  P* a* D  nExample52.6:ChangePointModels .....................3630
" H& b1 E2 X% h- r4 KExample52.7:ExponentialandWeibullSurvivalAnalysis ..........3634' B( h- q5 Z5 w( W/ l* X2 h
Example52.8:CoxModels ..........................3647
% I, s% V8 m! j; b* L. r9 PExample52.9:NormalRegressionwithIntervalCensoring .........3664+ R& b$ y$ B4 A6 k+ i/ e
Example52.10:ConstrainedAnalysis ....................3666- x7 s& C7 P% l1 R7 e) ?: m
Example52.11:ImplementaNewSamplingAlgorithm ...........3672
+ L7 p7 X+ T% y) ?+ ^/ zExample52.12:UsingaTransformationtoImproveMixing .........3683
9 b1 M1 k: f3 v: {& H# CExample52.13:Gelman-RubinDiagnostics .................3693
3 d9 D* `# N8 s/ C# s+ v, x: @1 G- RReferences ...................................... 3700" f8 w. V1 |# k) P  ^$ q; X

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作者: tbob228    时间: 2014-7-23 14:53
谢谢好人一枚5 C5 e; x5 P; X- Y1 R9 A( ]
作者: w785485068    时间: 2014-7-30 20:10
支持了。。。。。。。
作者: 破碎的风    时间: 2015-2-7 23:24
不错不错！
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作者: 本世界的大人    时间: 2015-9-4 15:46
谢谢分享，学习学习。。。。
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