winbugs出现trap 66 postcondition violated，问题出在哪里？

我认为最好能程序能执行2万次，取掉前后500次的结果，然后再做分析，
这样的结果比较准确，做出的结果比较漂亮。
另外，如果能把你模型的想法说清楚，例如：为什么U是变量？你的方程设定的目标及需要的结果？
相关的参考文献？
这样epoh老师就可以给您做更多的帮助！
另外，如果您把问题解决了，希望能说说如何解决的！

epoh 发表于 2011-12-1 19:47
change the prior by increasing the prior precision
can solve the problem.(trap 66 postcondition vio ...

老师您好！
我最近在做 winbugs 程序。出现了个问题想请教下您，model ，到初始化都可以，但是在update的过程中弹出 trap框，就走不了，我的代码入下：
# model volatility
{


d0<-exp(2*delta0)
d1<--0.5*d0

yisigma20<-1/(h0*(v/(v-2)))
y0~dt(alpha,yisigma20,v)
ymean[1]<-alpha+beta*y0
yisigma2[1]<-1/(h[1]*(v/(v-2)))
y[1]~dt( ymean[1],yisigma2[1],v)
    for(t in 2:100){
          ymean[t]<-alpha+beta*y[t-1]+pow(y[t-1],rou)*sqrt(y[t]-alpha-beta*y[t-1]-mm0/y[t-1])+jump[t]*bernsong[t]+mm0/y[t-1]
          yisigma2[t]<-1/(h[t]*(v/(v-2)))
           y[t]~dt( ymean[t],yisigma2[t],v)
          jump[t]<-exp(jump0[t])-1
          jump0[t]~dnorm(d1,d0)
         bernsong[t]~dbern(k)
                       }
  
   
alpha~dnorm(0,1)
beta~dnorm(0,1)
mu~dunif(0,1)
phi1~dunif(0,1)
phi2~dunif(0,1)
v~dunif(2,128)
mm0~dnorm(0,0.01)
delta0~dnorm(-3.07,0.149)
k~dbeta(2,100)
rou~dunif(0.5,1.9)
#deltaf~dgamma(2.5,0.025)



h0<-mu
h[1]<-mu+phi1*h0+phi2*(y0-alpha)*(y0-alpha)
h[2]<-mu+phi1*h[1]+phi2*(y[1]-alpha-beta*y0-mm0/y0)*(y[1]-alpha-beta*y0-mm0/y0)
     for(j in 3:100){
h[j]<-mu+phi1*h[j-1]+phi2*(y[j-1]-alpha-beta*y[j-2]-mm0/y[j-2])*(y[j-1]-alpha-beta*y[j-2]-mm0/y[j-2])

                 }
}
#data
list(
y=c(0.025594,0.025354,0.025174,0.025104,0.024904,0.024774,0.024664,0.024504,0.024414,0.024204,0.024244,0.024174,0.024164,0.023994,0.023974,0.023935,0.023865,0.023755,0.023725,0.023761,0.023725,0.023645,0.023625,0.023585,0.023575,0.023555,0.023395,0.023275,0.023295,0.023175,0.023225,0.023055,0.023115,0.023065,0.023005,0.023015,0.022995,0.023025,0.023075,0.023075,0.023005,0.023085,0.023285,0.023585,0.024114,0.025564,0.025534,0.024714,0.025124,0.025774,0.024694,0.025244,0.025244,0.025224,0.025044,0.024984,0.024964,0.024864,0.024654,0.024484,0.024234,0.024084,0.023954,0.023875,0.023735,0.023782,0.023825,0.023605,0.023415,0.023465,0.023265,0.022975,0.022952,0.022994,0.023021,0.023022,0.023018,0.022969,0.022919,0.022854,0.022777,0.02268,0.022535,0.022209,
0.022192,0.021606,0.021446,0.021381,0.021385,0.021385,0.021396,0.021379,0.021378,0.021385,0.021389,0.021386,0.021385,0.021372,0.021357,0.02135,0.021353,0.021363,0.019693,0.01958,0.019566,
0.019545,0.019533,0.019524,0.019517,0.019503,0.019501,0.019501,0.019505,0.019519,0.01951,0.019513,0.019514,0.019508,0.019508,
0.0195,0.019489,0.019491,0.019491,0.019489,0.019497,0.019501,
0.0195,0.019689,0.020278,0.020634,0.020979,0.022827,0.022944,
0.022492,0.022396,0.02236,0.022307,0.022313,0.022294,0.02228,
0.022282,0.022408,0.022956,0.023491,0.023576,0.023033,0.022741,0.022504,0.022607,0.022995,0.022628,0.022385,0.021467,0.020755,0.020536,0.020116,0.01978,0.0197,0.019526,0.019494,0.019601,
0.019922,0.02013,0.020396,0.021034,0.021326,0.021486,0.021695,
0.022439,0.02274,0.022395,0.021765,0.021436,0.021186,0.020986,
0.020876,0.021486,0.028602,0.028292,0.028142,0.028052,0.030411,0.03219,0.030481,0.029102,0.03275,0.030681,0.026543,0.022125,
0.021755,0.021546,0.021356,0.021296,0.021366,0.021286,0.021026,0.028432,0.027243,0.022915,0.021785,0.021116,0.020416,0.019656,0.019116,0.018517,0.018807,0.018627,0.018317,0.021055,0.024426,0.022749,0.021811,0.021112,0.021439,0.024878,0.023885,0.024174,0.024414,0.023922,0.022992,0.022073,0.024226,0.024064,0.022972,0.022419,0.022364,0.022226,0.021386,0.021051,0.020906,0.021331,0.022087,0.021574,0.020867,0.02218,0.021706,0.021381,0.019912,
0.019451,0.019079,0.018404,0.018383,0.018321,0.019086,0.018479,0.018247,0.018348,0.018419,0.023626,0.019763,0.018647,0.018393,0.018288,0.016901,0.015092,0.014132,0.01309,0.012702,0.012243,
0.01219,0.011573,0.011322,0.011241,0.010971,0.010929,0.010881,
0.010893,0.011288,0.011559,0.01191,0.012548,0.012289,0.012488,
0.012469,0.012356,0.012285,0.012075,0.012181,0.012016,0.01175,
0.011452,0.011195,0.011105,0.011194,0.011057,0.011184,0.011681,0.01315,0.015559,0.016228,0.015571,0.015064,0.015065,0.014853,
0.01456,0.014911,0.020212,0.014196,0.013372,0.013155,0.014121,
0.014222,0.014122,0.016274,0.016177,0.015668,0.015528,0.017336,0.021099,0.01748,0.016547,0.01615,0.017351,0.018108,0.020561,
0.020907,0.020805,0.020303,0.019952,0.026532,0.026846,0.026069,0.025307,0.023957,0.022225,0.022274,0.021171,0.020823,0.021921,0.023957,0.022473,0.024816,0.022967,0.024184,0.03184,0.038217,
0.038793,0.023691,0.022367,0.02034,0.021035,0.019499,0.014814,
0.013888,0.015965,0.020641,0.019712,0.041984,0.020652,0.016793,0.014783,0.015104,0.018557,0.019563,0.021791,0.024811,0.042072,0.032851,0.030155,0.025315,0.023425,0.028143,0.022956,0.043142,0.021866,0.029018,0.023655,0.030976,0.021117,0.02117,0.020254,
0.022554,0.019712,0.02429,0.024474,0.02852,0.057212,0.068364,
0.020222,0.022238,0.025188,0.102,0.030743,0.027296,0.020917,
0.027458,0.030807,0.024537,0.033433,0.021542,0.024812,0.027769,0.020272,0.026349,0.035388,0.029447,0.025864,0.038202,0.028134,0.02368,0.025489,0.024155,0.023903,0.028004,0.028383,0.028898,
0.029521,0.039154,0.034845,0.031309,0.033352,0.033399,0.031508,0.032519,0.029273,0.027659,0.031611,0.030267,0.037872,0.031574,0.027895,0.030999,0.029985,0.029655,0.030072,0.033736,0.034274,0.034304,0.030686,0.029982,0.027985,0.02792,0.027099,0.025185,
0.020991,0.01854,0.015396,0.014029,0.011759,0.009366,0.009163,
0.010209,0.009421,0.009681,0.009936,0.009447,0.009352,0.009498,0.009843,0.009761,0.009569,0.009503,0.009224,0.009729,0.009397,0.00956,0.009699,0.00945,0.009403,0.009932,0.011692,0.012441,
0.012281,0.015623,0.017149,0.01936,0.016028,0.014119,0.012642,
0.013953,0.017329,0.014394,0.015442,0.016266,0.016988,0.015278,0.014218,0.013396,0.014414,0.014832,0.014482,0.014609,0.015016,0.014813,0.014558,0.014625,0.013896,0.014224,0.014804,0.018636,0.017263,0.02556,0.016758,0.01693,0.016747,0.01638,0.015559,
0.015876,0.016926,0.016782,0.016995,0.016003,0.017085,0.017483,0.01825,0.023053,0.022063,0.027267,0.027321,0.03134,0.025967,
0.022847,0.018609,0.01779,0.01673,0.016934,0.017406,0.017477,
0.022609,0.023424,0.02289,0.01997,0.026823,0.019344,0.019384,
0.020161,0.016141,0.016975,0.020921,0.0272,0.033317,0.024854,
0.037192,0.05419,0.051686,0.028044,0.02529,0.074909,0.080092,
0.039141,0.02842,0.031447,0.022087,0.020523,0.020241,0.022814,
0.027831,0.024809,0.023617,0.035424,0.029438,0.02767,0.036063,
0.040768,0.043924,0.034699,0.046058,0.067023,0.084078,0.05893,
0.061433,0.041315,0.054042,0.050954,0.030142,0.030842,0.045151,0.040731,0.042123,0.036292,0.033175,0.04121,0.050204,0.031432,
0.034444,0.050413,0.034991,0.035037,0.037059,0.040388,0.036987,0.035227,0.030753,0.037346,0.055984


      )
)
#initial values
list(alpha=0.020676,beta=0.518890865,mu=0.3,phi1=0.1,phi2=0.1,v=3,y0=1,mm1=0,rou=1.4,delta0=0,k=0.5,mm0=0.00000000000000322)


万分谢谢老师

zhangtao 发表于 2011-12-2 09:45
model {
for (i in 1:N) {Y ~ dbern(p)
     logit(p)

zhangtao老师您好！
做 winbugs 程序。出现了个问题想请教下您，model ，到初始化都可以，但是在update的过程中弹出 trap框，就走不了，上面也问了epoh老师，希望您们能帮助下我，非常谢谢了。我的代码入下：
# model volatility
{


d0<-exp(2*delta0)
d1<--0.5*d0

yisigma20<-1/(h0*(v/(v-2)))
y0~dt(alpha,yisigma20,v)
ymean[1]<-alpha+beta*y0
yisigma2[1]<-1/(h[1]*(v/(v-2)))
y[1]~dt( ymean[1],yisigma2[1],v)
    for(t in 2:100){
          ymean[t]<-alpha+beta*y[t-1]+pow(y[t-1],rou)*sqrt(y[t]-alpha-beta*y[t-1]-mm0/y[t-1])+jump[t]*bernsong[t]+mm0/y[t-1]
          yisigma2[t]<-1/(h[t]*(v/(v-2)))
           y[t]~dt( ymean[t],yisigma2[t],v)
          jump[t]<-exp(jump0[t])-1
          jump0[t]~dnorm(d1,d0)
         bernsong[t]~dbern(k)
                       }
  
   
alpha~dnorm(0,1)
beta~dnorm(0,1)
mu~dunif(0,1)
phi1~dunif(0,1)
phi2~dunif(0,1)
v~dunif(2,128)
mm0~dnorm(0,0.01)
delta0~dnorm(-3.07,0.149)
k~dbeta(2,100)
rou~dunif(0.5,1.9)
#deltaf~dgamma(2.5,0.025)



h0<-mu
h[1]<-mu+phi1*h0+phi2*(y0-alpha)*(y0-alpha)
h[2]<-mu+phi1*h[1]+phi2*(y[1]-alpha-beta*y0-mm0/y0)*(y[1]-alpha-beta*y0-mm0/y0)
     for(j in 3:100){
h[j]<-mu+phi1*h[j-1]+phi2*(y[j-1]-alpha-beta*y[j-2]-mm0/y[j-2])*(y[j-1]-alpha-beta*y[j-2]-mm0/y[j-2])

                 }
}
#data
list(
y=c(0.025594,0.025354,0.025174,0.025104,0.024904,0.024774,0.024664,0.024504,0.024414,0.024204,0.024244,0.024174,0.024164,0.023994,0.023974,0.023935,0.023865,0.023755,0.023725,0.023761,0.023725,0.023645,0.023625,0.023585,0.023575,0.023555,0.023395,0.023275,0.023295,0.023175,0.023225,0.023055,0.023115,0.023065,0.023005,0.023015,0.022995,0.023025,0.023075,0.023075,0.023005,0.023085,0.023285,0.023585,0.024114,0.025564,0.025534,0.024714,0.025124,0.025774,0.024694,0.025244,0.025244,0.025224,0.025044,0.024984,0.024964,0.024864,0.024654,0.024484,0.024234,0.024084,0.023954,0.023875,0.023735,0.023782,0.023825,0.023605,0.023415,0.023465,0.023265,0.022975,0.022952,0.022994,0.023021,0.023022,0.023018,0.022969,0.022919,0.022854,0.022777,0.02268,0.022535,0.022209,
0.022192,0.021606,0.021446,0.021381,0.021385,0.021385,0.021396,0.021379,0.021378,0.021385,0.021389,0.021386,0.021385,0.021372,0.021357,0.02135,0.021353,0.021363,0.019693,0.01958,0.019566,
0.019545,0.019533,0.019524,0.019517,0.019503,0.019501,0.019501,0.019505,0.019519,0.01951,0.019513,0.019514,0.019508,0.019508,
0.0195,0.019489,0.019491,0.019491,0.019489,0.019497,0.019501,
0.0195,0.019689,0.020278,0.020634,0.020979,0.022827,0.022944,
0.022492,0.022396,0.02236,0.022307,0.022313,0.022294,0.02228,
0.022282,0.022408,0.022956,0.023491,0.023576,0.023033,0.022741,0.022504,0.022607,0.022995,0.022628,0.022385,0.021467,0.020755,0.020536,0.020116,0.01978,0.0197,0.019526,0.019494,0.019601,
0.019922,0.02013,0.020396,0.021034,0.021326,0.021486,0.021695,
0.022439,0.02274,0.022395,0.021765,0.021436,0.021186,0.020986,
0.020876,0.021486,0.028602,0.028292,0.028142,0.028052,0.030411,0.03219,0.030481,0.029102,0.03275,0.030681,0.026543,0.022125,
0.021755,0.021546,0.021356,0.021296,0.021366,0.021286,0.021026,0.028432,0.027243,0.022915,0.021785,0.021116,0.020416,0.019656,0.019116,0.018517,0.018807,0.018627,0.018317,0.021055,0.024426,0.022749,0.021811,0.021112,0.021439,0.024878,0.023885,0.024174,0.024414,0.023922,0.022992,0.022073,0.024226,0.024064,0.022972,0.022419,0.022364,0.022226,0.021386,0.021051,0.020906,0.021331,0.022087,0.021574,0.020867,0.02218,0.021706,0.021381,0.019912,
0.019451,0.019079,0.018404,0.018383,0.018321,0.019086,0.018479,0.018247,0.018348,0.018419,0.023626,0.019763,0.018647,0.018393,0.018288,0.016901,0.015092,0.014132,0.01309,0.012702,0.012243,
0.01219,0.011573,0.011322,0.011241,0.010971,0.010929,0.010881,
0.010893,0.011288,0.011559,0.01191,0.012548,0.012289,0.012488,
0.012469,0.012356,0.012285,0.012075,0.012181,0.012016,0.01175,
0.011452,0.011195,0.011105,0.011194,0.011057,0.011184,0.011681,0.01315,0.015559,0.016228,0.015571,0.015064,0.015065,0.014853,
0.01456,0.014911,0.020212,0.014196,0.013372,0.013155,0.014121,
0.014222,0.014122,0.016274,0.016177,0.015668,0.015528,0.017336,0.021099,0.01748,0.016547,0.01615,0.017351,0.018108,0.020561,
0.020907,0.020805,0.020303,0.019952,0.026532,0.026846,0.026069,0.025307,0.023957,0.022225,0.022274,0.021171,0.020823,0.021921,0.023957,0.022473,0.024816,0.022967,0.024184,0.03184,0.038217,
0.038793,0.023691,0.022367,0.02034,0.021035,0.019499,0.014814,
0.013888,0.015965,0.020641,0.019712,0.041984,0.020652,0.016793,0.014783,0.015104,0.018557,0.019563,0.021791,0.024811,0.042072,0.032851,0.030155,0.025315,0.023425,0.028143,0.022956,0.043142,0.021866,0.029018,0.023655,0.030976,0.021117,0.02117,0.020254,
0.022554,0.019712,0.02429,0.024474,0.02852,0.057212,0.068364,
0.020222,0.022238,0.025188,0.102,0.030743,0.027296,0.020917,
0.027458,0.030807,0.024537,0.033433,0.021542,0.024812,0.027769,0.020272,0.026349,0.035388,0.029447,0.025864,0.038202,0.028134,0.02368,0.025489,0.024155,0.023903,0.028004,0.028383,0.028898,
0.029521,0.039154,0.034845,0.031309,0.033352,0.033399,0.031508,0.032519,0.029273,0.027659,0.031611,0.030267,0.037872,0.031574,0.027895,0.030999,0.029985,0.029655,0.030072,0.033736,0.034274,0.034304,0.030686,0.029982,0.027985,0.02792,0.027099,0.025185,
0.020991,0.01854,0.015396,0.014029,0.011759,0.009366,0.009163,
0.010209,0.009421,0.009681,0.009936,0.009447,0.009352,0.009498,0.009843,0.009761,0.009569,0.009503,0.009224,0.009729,0.009397,0.00956,0.009699,0.00945,0.009403,0.009932,0.011692,0.012441,
0.012281,0.015623,0.017149,0.01936,0.016028,0.014119,0.012642,
0.013953,0.017329,0.014394,0.015442,0.016266,0.016988,0.015278,0.014218,0.013396,0.014414,0.014832,0.014482,0.014609,0.015016,0.014813,0.014558,0.014625,0.013896,0.014224,0.014804,0.018636,0.017263,0.02556,0.016758,0.01693,0.016747,0.01638,0.015559,
0.015876,0.016926,0.016782,0.016995,0.016003,0.017085,0.017483,0.01825,0.023053,0.022063,0.027267,0.027321,0.03134,0.025967,
0.022847,0.018609,0.01779,0.01673,0.016934,0.017406,0.017477,
0.022609,0.023424,0.02289,0.01997,0.026823,0.019344,0.019384,
0.020161,0.016141,0.016975,0.020921,0.0272,0.033317,0.024854,
0.037192,0.05419,0.051686,0.028044,0.02529,0.074909,0.080092,
0.039141,0.02842,0.031447,0.022087,0.020523,0.020241,0.022814,
0.027831,0.024809,0.023617,0.035424,0.029438,0.02767,0.036063,
0.040768,0.043924,0.034699,0.046058,0.067023,0.084078,0.05893,
0.061433,0.041315,0.054042,0.050954,0.030142,0.030842,0.045151,0.040731,0.042123,0.036292,0.033175,0.04121,0.050204,0.031432,
0.034444,0.050413,0.034991,0.035037,0.037059,0.040388,0.036987,0.035227,0.030753,0.037346,0.055984


      )
)
#initial values
list(alpha=0.020676,beta=0.518890865,mu=0.3,phi1=0.1,phi2=0.1,v=3,y0=1,mm1=0,rou=1.4,delta0=0,k=0.5,mm0=0.00000000000000322)


万分谢谢老师

undefined real result

Math.Sqrt   [00000120H]
        .x        REAL        -13.18914409111797
GraphStack.Node.Value   [00000FE9H]
        .i        INTEGER        19
        .j        INTEGER        6
        .k        INTEGER        5
        .node        GraphStack.Node        [011462E0H]
        .op        INTEGER        23
        .p        GraphNodes.Node        [01176BB0H]
        .top        INTEGER        2
        .work        ARRAY 10 OF REAL        Elements
GraphT.Node.Likelihood   [00000712H]
        .lambda        REAL        0.0
        .logLambda        REAL        0.01
        .logLikelihood        REAL        0.2231299172210023
        .logTau        REAL        3.065529831432839E-303
        .mu        REAL        5.255114088343153E-308
        .node        GraphT.Node        [0117E100H]
        .tau        REAL        8.487983573935575E-314
        .x        REAL        0.02135
GraphStochastic.Node.Conditional   [000004BCH]
        .likelihood        GraphStochastic.List        [0125E990H]
        .log        REAL        -2.489347997952568E-4
        .node        GraphStochastic.Node        [01176BB0H]
UpdaterMetnormal.Updater.MCMC   [000001B8H]
        .alpha        REAL        2.122045197035791E-314
        .newDen        REAL        5.338947044029618E-315
        .newVal        REAL        0.2231299172210023
        .oldDen        REAL        -30.40847927996916
        .oldVal        REAL        -0.08627110712337649
        .overRelax        BOOLEAN        FALSE
        .prior        GraphStochastic.Node        [01176BB0H]
        .rate        REAL        4.839867702782698E-276
        .res        INTEGER        0
        .updater        UpdaterMetnormal.Updater        [012782A0H]
BugsUpdaters.Updater.MCMC   [000005B8H]
        .chain        INTEGER        0
        .depth        INTEGER        1
        .i        INTEGER        0
        .name        BugsNames.Name        [01123220H]
        .ok        BOOLEAN        TRUE
        .overRelax        BOOLEAN        FALSE
        .res        INTEGER        0
        .size        INTEGER        1
        .string        ARRAY 120 OF CHAR        0B5B0X, 93ECX, 5946X, 3FD0X, 6108X, 498FX, 6C22X, 0BFE3X, 75C2X, 811BX, 3980X, 0C001X, 0AD14X, 1C94X, 83E4X, 3FA4X, 10B2X, 6365X, 321EX, 43E5X, 3550X, 3F9AX, 8E50X, 97C9X, 838EX, 3FE0X, 6E2X, 3233X, 4E98X, 3FC3X, 8E50X, 97C9X   ...
        .updater        BugsUpdaters.Updater        [01278250H]
BugsSampler.MCMC   [0000036DH]
        .chain        INTEGER        0
        .cursor        BugsSampler.List        [012782D0H]
        .depth        INTEGER        1
        .depth0        INTEGER        1
        .depth1        INTEGER        4
        .offset        INTEGER        18928464
        .ok        BOOLEAN        TRUE
        .overRelax        BOOLEAN        FALSE
        .updater        BugsUpdaters.Updater        [01278250H]
BugsCmds.Action.Step   [00000B1FH]
        .a        BugsCmds.Action        [011C68B0H]
        .chain        INTEGER        0
        .i        INTEGER        15
        .j        INTEGER        0
        .numChains        INTEGER        1
BugsCmds.Action.Do   [00000C58H]
        .a        BugsCmds.Action        [011C68B0H]
        .elapsedTime        LONGINT        63E521F163E40384H
        .profileList        ARRAY 2024 OF CHAR        ""   ...
        .res        INTEGER        1639404127
        .s        ARRAY 120 OF CHAR        ""   ...
Services.Exec   [00000136H]
        .a        Services.Action        [011C68B0H]
        .t        POINTER        [63E40384H]
Services.IterateOverActions   [000002F4H]
        .p        Services.Action        [011C68B0H]
        .t        POINTER        NIL
        .time        LONGINT        969515
Services.StdHook.Step   [0000034DH]
        .h        Services.StdHook        [0111E380H]
HostWindows.Idle   [00004A86H]
        .focus        BOOLEAN        FALSE
        .tick        Controllers.TickMsg        Fields
        .w        HostWindows.Window        NIL
HostMenus.TimerTick   [00003422H]
        .lParam        INTEGER        0
        .ops        Controllers.PollOpsMsg        Fields
        .wParam        INTEGER        1
        .wnd        INTEGER        131790
Kernel.Try   [00003A61H]
        .a        INTEGER        131790
        .b        INTEGER        1
        .c        INTEGER        0
        .h        PROCEDURE        HostMenus.TimerTick
HostMenus.ApplWinHandler   [00003841H]
        .Proc        PROCEDURE        NIL
        .hit        BOOLEAN        FALSE
        .lParam        INTEGER        0
        .message        INTEGER        275
        .res        INTEGER        65758
        .s        ARRAY 256 OF SHORTCHAR        1X   ...
        .w        INTEGER        1629125088
        .wParam        INTEGER        1
        .wnd        INTEGER        131790
<system>   (pc=77D18733H,  fp=0022FB84H)
<system>   (pc=77D18815H,  fp=0022FBECH)
<system>   (pc=77D189CCH,  fp=0022FC4CH)
<system>   (pc=77D196C6H,  fp=0022FC5CH)
HostMenus.Loop   [00003BDEH]
        .done        BOOLEAN        FALSE
        .f        SET        {0..5}
        .n        INTEGER        2
        .res        INTEGER        0
        .w        HostWindows.Window        NIL
Kernel.Start   [00002B8CH]
        .code        PROCEDURE        HostMenus.Loop

由于这个程序问题比较多，等我好好思考试试再说！

model is syntactically correct
expected variable name
model is syntactically correct
data loaded
model compiled
expected variable name
undefined variable
initial values generated, model initialized
expected variable name
alpha
alpha GraphNormal.StdNode
alpha UpdaterMetnormal.Updater
alpha      2.745372382736294
初步判断是某一个变量没有定义，得好好找找

zhangtao 发表于 2012-2-10 09:17
model is syntactically correct
expected variable name
model is syntactically correct

老师，您好，我也存在类似问题，模型前面几步骤都OK，就是最后不能updating了，请麻烦老师看看问题出在哪里？怎么样可以修改正确了？谢谢老师。model
{
   alpha ~ dnorm(5,50)
   blpha ~ dnorm(5,50)
   for( i in 1 : N ) {
      p ~ dbeta(alpha,blpha)
   }
   for( i in 1 : N ) {
      r ~ dbin(p,n)
   }
   feta <- 1 / (1 + alpha + blpha)
}
list(N=47,n=c(1,9,10,6,17,12,9,5,5,2,1,10,1,15,9,12,4,7,8,8,9,2,12,8,4,5,8,9,13,3,2,9,5,3,6,2,3,4,7,5,6,8,6,5,4,4,1),r=c(0,0,0,1,2,1,1,0,1,1,1,2,1,2,1,2,1,2,5,1,4,1,0,1,2,4,2,4,6,1,2,1,1,3,4,2,1,3,3,2,3,5,3,3,3,3,1),p=c(0,0,0,0.167,0.118,0.083,0.111,0,0.2,0.5,1,0.2,1,0.133,0.111,0.167,0.25,0.286,0.625,0.125,0.444,0.5,0,0.125,0.5,0.8,0.25,0.444,0.462,0.333,1,0.111,0.2,1,0.667,1,0.333,0.75,0.429,0.4,0.5,0.625,0.5,0.6,0.75,0.75,1))
list(alpha=1,blpha=1)
前面所有的步骤都OK 但是最后updating时出现了错误：“sorry something went wrong in procedure UpdaterStd.Sample”，也就是通常说的最后无法updating。
本文来自: 人大经济论坛 S-Plus&R专版 版，详细出处参考： https://bbs.pinggu.org/forum.php? ... =2541191&page=1

epoh 发表于 2011-12-2 18:42
程序已经由不能执行
到能执行3000次
显示prior的设置很重要

您好，请问对prior的设置有没有一些可以遵循的规则？
谢谢！