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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
9 h& d) w$ w% b6 m$ c/ mTheMCMCProcedure7 p: f8 s: P; o# ~
Contents$ ?6 `+ U8 u. d$ L5 [1 X; q6 Q
Overview:MCMCProcedure ............................ 3478) r  @, |% C2 L
PROCMCMCComparedwithOtherSASProcedures ............3479
$ u3 s( h$ a% `% X7 F7 \2 b9 h" MGettingStarted:MCMCProcedure .......................... 3479
7 M9 }! I& G+ YSimpleLinearRegression ...........................3480* t8 F3 F  G( v
TheBehrens-FisherProblem ..........................34888 V5 N; ?* r: e" \2 v6 N
Mixed-EffectsModel .............................3492! @% X  O0 I2 g
Syntax:MCMCProcedure .............................. 3495
" c5 N$ {* W7 b% w* LPROCMCMCStatement ...........................3496
6 W% H  T/ h5 A) Y4 GARRAYStatement ...............................3508" @7 k* ~& `* B/ L
BEGINCNST/ENDCNSTStatement .....................3509' O+ V- ?6 A- R
BEGINNODATA/ENDNODATAStatements .................3511
+ g5 n0 K3 |' g! `9 {: v$ A* mBYStatement .................................3511' t+ R$ r) {8 i7 h# {
MODELStatement ...............................3512/ M2 F4 c& Z) n
PARMSStatement ...............................3515# d. ^& L5 U; N; A# d2 Q/ m
PRIOR/HYPERPRIORStatement .......................3516
" G3 i$ d* T* _0 S1 EProgrammingStatements ...........................3516
" G$ J; D3 m$ Y4 i$ u. G. |' rUDSStatement .................................3518
2 p/ q8 O5 h9 ~& j/ MDetails:MCMCProcedure .............................. 3522
; f% m3 B. _6 b# r# k8 V8 UHowPROCMCMCWorks ..........................3522
9 U( `; d0 W) z2 KBlockingofParameters ............................3523
1 [* ~( f  k/ j; ESamplers ....................................35242 S+ |5 a# \* J0 V% U
TuningtheProposalDistribution .......................3525: m+ e7 W  A6 C( h* @' u# H
InitialValuesoftheMarkovChains ......................35288 m( o" w8 c- W4 {. J! w% u1 a2 N
AssignmentsofParameters ..........................3528  g: K% |+ Q$ ?% J( G( k
StandardDistributions .............................35305 p9 r9 `; O7 k7 @/ R, a3 J# z
SpecifyingaNewDistribution .........................3541
8 _, _( x7 j4 ~& c6 Z7 ^UsingDensityFunctionsintheProgrammingStatements ...........3542( }* y) n5 M8 r$ j0 h
TruncationandCensoring ...........................35446 J  h1 Z. [# Y, |  G& h& f
MultivariateDensityFunctions ........................3546# g/ {8 o2 M% ]9 H# f: {6 o
SomeUsefulSASFunctions ..........................3549
  W+ D& h1 p$ t) R3 Q: \2 MMatrixFunctionsinPROCMCMC ......................3551, G- j* u) l: v
ModelingJointLikelihood ...........................3556- S6 h$ z$ e6 `7 n$ e
RegeneratingDiagnosticsPlots ........................3557- Y/ w2 T) x/ f5 _2 P
PosteriorPredictiveDistribution ........................35604 s7 {. {+ l0 ~' B* W
HandlingofMissingData ...........................3565
: y1 `" U, ~0 ^FloatingPointErrorsandOverflows ......................3565
; H3 S- K, R( S: X6 h/ \HandlingErrorMessages ...........................3568
1 \# h$ I" M' @# v, v- [2 s- H  MComputationalResources ...........................3570
' T+ x3 \. N! pDisplayedOutput ................................3571
! l( Q4 v+ {7 _+ o% j% xODSTableNames ...............................3575
( ~. a8 b: l1 n1 `, ?+ t& H- RODSGraphics .................................3577" a' t' r* I: |. _: F0 v5 ~
Examples:MCMCProcedure ............................ 3578# N+ m4 X8 M8 i
Example52.1:SimulatingSamplesFromaKnownDensity .........3578
% G  G$ z0 A) [  W/ r! M# gExample52.2:Box-CoxTransformation ...................35836 I  y3 W* H$ F+ z' \
Example52.3:GeneralizedLinearModels ..................3592/ A: B8 n6 c6 ]- V) p3 x  T; s
Example52.4:NonlinearPoissonRegressionModels ............3605. |5 y7 h5 u0 S0 ~8 `
Example52.5:Random-EffectsModels ...................3614
! {7 H1 j# c" dExample52.6:ChangePointModels .....................3630
6 ^2 y; G6 @1 S$ O9 @; P/ mExample52.7:ExponentialandWeibullSurvivalAnalysis ..........36348 n$ B  e% C* L5 q' J
Example52.8:CoxModels ..........................3647: k3 w1 m" f) o# Q. w
Example52.9:NormalRegressionwithIntervalCensoring .........3664
1 o/ \  I# W5 [  s6 e- |, X1 wExample52.10:ConstrainedAnalysis ....................36667 l/ n7 ~  h: \, Q+ e1 i! m: r0 @
Example52.11:ImplementaNewSamplingAlgorithm ...........36720 P. [2 ]5 \. _4 I( P
Example52.12:UsingaTransformationtoImproveMixing .........3683
& B& u4 l7 O" c+ B4 q% mExample52.13:Gelman-RubinDiagnostics .................3693: W( e9 s* @1 p3 e* U1 ?
References ...................................... 3700
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作者: tbob228    时间: 2014-7-23 14:53
谢谢好人一枚
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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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