用于复制

Question

我试图通过Mark the Ballot用一段jags代码复制模拟，但jags正在向我发送错误信息..

如果我理解正确的话，它应该在某处为每一方索引房屋效应时出现问题，但我找不到它，因为该节点似乎已被编入索引。有谁知道错误是什么样的？

model <- jags.model(textConnection(model),
                       data = data,
                       n.chains=4,
                       n.adapt=10000


    Compiling model graph
       Resolving undeclared variables
       Allocating nodes
    Deleting model

    Error in jags.model(textConnection(model2), data = data, n.chains = 4,  :
      RUNTIME ERROR:
    Cannot insert node into houseEffect[1...4,2]. Dimension mismatch

用于复制

model <- '
    model {
    for(poll in 1:NUMPOLLS) {
    adjusted_poll[poll, 1:PARTIES] <- walk[pollDay[poll], 1:PARTIES] +
    houseEffect[house[poll], 1:PARTIES]
    primaryVotes[poll, 1:PARTIES] ~ dmulti(adjusted_poll[poll, 1:PARTIES], n[poll])
    }
    tightness <- 50000
    discontinuity_tightness <- 50

    for(day in 2:(discontinuity-1)) {
    multinomial[day, 1:PARTIES] <- walk[day-1,  1:PARTIES] * tightness
    walk[day, 1:PARTIES] ~ ddirch(multinomial[day, 1:PARTIES])
    }
    multinomial[discontinuity, 1:PARTIES] <- walk[discontinuity-1,  1:PARTIES] * discontinuity_tightness
    walk[discontinuity, 1:PARTIES] ~ ddirch(multinomial[discontinuity, 1:PARTIES])

    for(day in discontinuity+1:PERIOD) {
    multinomial[day, 1:PARTIES] <- walk[day-1,  1:PARTIES] * tightness
    walk[day, 1:PARTIES] ~ ddirch(multinomial[day, 1:PARTIES])
    }

    for (party in 1:2) {
    alpha[party] ~ dunif(250, 600) 
    }
    for (party in 3:PARTIES) {
    alpha[party] ~ dunif(10, 250)
    }
    walk[1, 1:PARTIES] ~ ddirch(alpha[])

    for(day in 1:PERIOD) {
    CoalitionTPP[day] <- sum(walk[day, 1:PARTIES] *
    preference_flows[1:PARTIES])
    }

    for (party in 2:PARTIES) { 
    houseEffect[1, party] <- -sum( houseEffect[2:HOUSECOUNT, party] )
    }
    for(house in 1:HOUSECOUNT) { 
    houseEffect[house, 1] <- -sum( houseEffect[house, 2:PARTIES] )
    }
    # but note, we do not apply a double constraint to houseEffect[1, 1]
    monitorHouseEffectOneSumParties <- sum(houseEffect[1, 1:PARTIES])
    monitorHouseEffectOneSumHouses <- sum(houseEffect[1:HOUSECOUNT, 1])

    for (party in 2:PARTIES) {
    for(house in 2:HOUSECOUNT) { 
    houseEffect[house, party] ~ dnorm(0, pow(0.1, -2))
    } } }
    '

    preference_flows <- c(1.0, 0.0, 0.1697, 0.533)

    PERIOD = 26
    HOUSECOUNT = 5
    NUMPOLLS = 35
    PARTIES = 4
    discontinuity = 20

    pollDay = c(1, 1, 2, 2, 6, 8, 8, 9, 9, 10, 10, 10, 10, 12, 12, 13, 14, 14, 16, 16, 17, 18, 19, 19, 20, 21, 22, 22, 24, 24, 24, 24, 24, 26, 26)

    house = c(1, 2, 3, 4, 3, 3, 5, 1, 2, 1, 3, 4, 5, 3, 4, 2, 3, 4, 3, 4, 5, 3, 2, 4, 3, 5, 3, 4, 1, 2, 3, 4, 5, 3, 4)

    n = c(1400, 1400, 1000, 1155, 1000, 1000, 3690, 1400, 1400, 1400, 1000, 1177, 3499, 1000, 1180, 1400, 1000, 1161, 1000, 1148, 2419, 1000, 1386, 1148, 1000, 2532, 1000, 1172, 1682, 1402, 1000, 1160, 3183, 1000, 1169)

    preference_flows = c(1.0000, 0.0000, 0.1697, 0.5330)

    primaryVotes  = read.csv(text = c(
    'Coalition, Labor, Greens, Other
    532,574,154,140
    560,518,168,154
    350,410,115,125
    439,450,139,127
    385,385,95,135
    375,395,120,110
    1465,1483,417,325
    504,602,154,140
    532,560,154,154
    504,602,154,140
    355,415,120,110
    412,483,141,141
    1345,1450,392,312
    375,405,100,120
    448,448,142,142
    588,504,168,140
    390,380,115,115
    441,453,139,128
    380,400,110,110
    471,425,126,126
    957,979,278,205
    405,360,125,110
    546,532,182,126
    471,413,126,138
    385,380,120,115
    1008,995,301,228
    400,375,115,110
    457,410,141,164
    690,656,185,151
    603,491,182,126
    415,355,125,105
    464,429,139,128
    1307,1218,385,273
    410,370,130,90
    479,433,152,105'), sep=",")

    data = list(PERIOD = PERIOD,
                HOUSECOUNT = HOUSECOUNT,
                NUMPOLLS = NUMPOLLS,
                PARTIES = PARTIES,
                primaryVotes = primaryVotes,
                pollDay = pollDay,
                house = house,
                discontinuity = discontinuity,
                # manage rounding issues with df$Sample ...
                n = rowSums(primaryVotes),
                preference_flows = preference_flows
    )
    print(data)

Answer 1

问题在于您将房屋作为参数传递给模型，并且您在循环中使用房屋变量。 JAGS 4.0.1很困惑。如果你重新编码以取代＆＃34; house＆＃34;在（例如）＆＃34; h＆＃34;它应该工作......例子如下......

for (h in 2:HOUSECOUNT) { 
    for (p in 2:PARTIES) { 
        # vague priors ...
        houseEffect[h, p] ~ dnorm(0, pow(0.1, -2))
   }
}
for (p in 2:PARTIES) { 
    houseEffect[1, p] <- -sum( houseEffect[2:HOUSECOUNT, p] )
}
for(h in 1:HOUSECOUNT) { 
    houseEffect[h, 1] <- -sum( houseEffect[h, 2:PARTIES] )
}

无法将节点插入... []。尺寸不匹配

用于复制

1 个答案: