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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
7 }* m2 N* F- {- q: q+ A* y0 zTheMCMCProcedure
6 }/ M1 ?/ l, Z* `) W* d* sContents  U: a- e6 n9 J2 T; j( I
Overview:MCMCProcedure ............................ 3478# ^% {' Q3 A& p; o+ |
PROCMCMCComparedwithOtherSASProcedures ............3479
; s3 X% \. D% ?2 H$ wGettingStarted:MCMCProcedure .......................... 34797 H! W& h7 f% {
SimpleLinearRegression ...........................34804 F% W3 E) V# g6 _6 W
TheBehrens-FisherProblem ..........................34882 v( P9 }8 H! M6 ~, C
Mixed-EffectsModel .............................3492
& U# i# ?3 ~+ @. S  F" n- O, kSyntax:MCMCProcedure .............................. 3495
  y8 X7 t" D7 l3 Q& S" u8 p4 q* HPROCMCMCStatement ...........................3496# D- I+ z; J5 E# t. v
ARRAYStatement ...............................3508
6 \! h1 n' c. ]4 `- DBEGINCNST/ENDCNSTStatement .....................35090 L8 `% F' Z3 K* y0 ?5 T
BEGINNODATA/ENDNODATAStatements .................3511/ h9 J7 w3 S  V
BYStatement .................................3511% P5 L0 [+ H6 f7 l4 w) Q% M- T/ A( y
MODELStatement ...............................3512
- N+ m1 m+ k$ B  u$ y: _' MPARMSStatement ...............................3515
5 Z: Z5 t( c6 f  W' v  c. H- ^$ o; LPRIOR/HYPERPRIORStatement .......................3516
; |* d# G* g; j, QProgrammingStatements ...........................35165 ]5 B# ~: N% Z6 p0 t
UDSStatement .................................3518
2 g' k* R9 _* X  r+ q) A" g2 nDetails:MCMCProcedure .............................. 3522
. g. x2 E5 d" [6 K  y  ^; {HowPROCMCMCWorks ..........................35223 N$ o3 Z2 }' \/ J* N! [
BlockingofParameters ............................3523' `, t4 t+ B$ p8 h; Q0 t5 w3 E
Samplers ....................................35247 ?) U3 M6 G+ L- N/ R7 I( `* Z
TuningtheProposalDistribution .......................35252 W0 L) X2 a# {" K4 T( d  R: z
InitialValuesoftheMarkovChains ......................35286 _' s0 l* \! c. n; O& Z$ x9 ^
AssignmentsofParameters ..........................35280 u* g- ?* Z0 D2 s
StandardDistributions .............................3530) U- O& F3 Z" F) l' X" s
SpecifyingaNewDistribution .........................3541
) c2 p6 [4 z$ m/ ^2 y0 A8 q2 n0 G* NUsingDensityFunctionsintheProgrammingStatements ...........35424 \6 O8 n- d# U1 K: I" p
TruncationandCensoring ...........................3544  O& o$ h# }4 c0 K/ |+ _6 }2 B
MultivariateDensityFunctions ........................3546
  q: B) E# h/ F, ~SomeUsefulSASFunctions ..........................3549
% N% [7 m9 L6 `3 PMatrixFunctionsinPROCMCMC ......................35515 @1 q# B" f2 i: y
ModelingJointLikelihood ...........................3556% d# |  g7 v- e; O
RegeneratingDiagnosticsPlots ........................3557. u$ g7 ~9 P+ Q3 o* b2 G
PosteriorPredictiveDistribution ........................35608 e# F, U# q% |, A
HandlingofMissingData ...........................3565
& P& U' S% |: D1 L3 T4 eFloatingPointErrorsandOverflows ......................35653 X3 T. u  \' ~" P; D/ N4 ^
HandlingErrorMessages ...........................3568) u9 Z7 a" e6 i& d
ComputationalResources ...........................3570& s% Y! n% N; u
DisplayedOutput ................................3571
  |2 a7 Q3 D# zODSTableNames ...............................3575
, A0 }$ _5 ]0 p  p6 e3 j3 WODSGraphics .................................35777 O( s, ?" [/ |7 e
Examples:MCMCProcedure ............................ 3578
, {+ p- Z% u  Z/ l( p; K6 WExample52.1:SimulatingSamplesFromaKnownDensity .........3578* G' [' }- c+ y( t! w
Example52.2:Box-CoxTransformation ...................35839 M  e, w1 O5 }, Q0 o' e% U
Example52.3:GeneralizedLinearModels ..................3592& {, q: n" A* M# c2 q  n* u% C
Example52.4:NonlinearPoissonRegressionModels ............3605
8 Y+ r% N( K3 N5 r' ~( g7 A) eExample52.5:Random-EffectsModels ...................3614' F$ J4 d2 K( s6 N6 E- Q
Example52.6:ChangePointModels .....................3630
- S, z) l( ^" n) p) W- p; E) r! kExample52.7:ExponentialandWeibullSurvivalAnalysis ..........3634
. G1 y6 H2 b4 y5 r( q8 J: y3 dExample52.8:CoxModels ..........................3647* m) X! F- [& u+ D
Example52.9:NormalRegressionwithIntervalCensoring .........36648 [5 x# A' E* J) Y; N  p! L
Example52.10:ConstrainedAnalysis ....................3666+ ?) f9 L# j9 h% i
Example52.11:ImplementaNewSamplingAlgorithm ...........36720 y5 v5 d0 I% h) f
Example52.12:UsingaTransformationtoImproveMixing .........3683
9 v' q( `  g7 d2 w- c  B! VExample52.13:Gelman-RubinDiagnostics .................3693
) N) Y! @4 E  u7 g, YReferences ...................................... 3700. i! t% p/ ^; D0 g

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作者: tbob228    时间: 2014-7-23 14:53
谢谢好人一枚) Q+ @: @& y) {3 i2 C7 Y
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。。。。" W9 N( ]: w0 ~- X$ n




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