Rjags 编译错误尺寸不匹配

Question

我正在尝试编写二项式贝叶斯模型，但出现以下错误：

checkForRemoteErrors(val) 中的错误： 3个节点产生错误；第一个错误：运行时错误：第 15 行出现编译错误。 y
子集表达式中的维度不匹配

这是模型：

sink(file = "JAGS_survival_species.txt")  

cat("
  model {

  for (j in 1:Nsp) {  ## loop through species
  
      #### Likelihood              
  
      for (i in 1:N) {  
  
      #### ecological model
      logit(p[i, j]) <- b0[j] + b1[j] * log(HT_m[i]) + b2[j] * log(PREVDIA_cm[i]) + 
                     b3[j] * PREVDIA_cm[i] + b4[j] * ANN_DIA_GROWTH_cm[i]
  
      #### observation model
      y[i, j] ~ dbinom(p[i, j], N)
   
    }
      
      #### Priors at species level  -- all priors normal with a separate mean and sd
      b0[j] ~ dnorm(mu.b0, tau.b0)  
      b1[j] ~ dnorm(mu.b1, tau.b1)
      b2[j] ~ dnorm(mu.b2, tau.b2)
      b3[j] ~ dnorm(mu.b3, tau.b3)
      b4[j] ~ dnorm(mu.b4, tau.b4)

  }
  
  ####################################################################
  # hyperpriors (hierarchical model)
  
  mu.b0  ~  dunif(-10, 10)         # flat hyperpriors - for mu between -10 and 10
  mu.b1  ~  dunif(-10, 10)
  mu.b2  ~  dunif(-10, 10)
  mu.b3  ~  dunif(-10, 10)
  mu.b4  ~  dunif(-10, 10)
  
  sd.b0 ~ dunif(0, 5)
  tau.b0 <- 1/sd.b0^2
  
  sd.b1 ~ dunif(0, 5)
  tau.b1 <- 1/sd.b1^2
  
  sd.b2 ~ dunif(0, 5)
  tau.b2 <- 1/sd.b2^2
  
  sd.b3 ~ dunif(0, 5)
  tau.b3 <- 1/sd.b3^2
  
  sd.b4 ~ dunif(0, 5)
  tau.b4 <- 1/sd.b4^2
  
  } # end model
  ",fill = TRUE) 

sink()

以下是我正在使用的数据集的前 500 个观察结果：

ds <- structure(list(STATUSCD = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 
1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 
1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 
1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 
1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 
1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 
1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 
0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 
1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 
0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 
1, 1, 1, 1, 0, 1), SPCD = c(7911, 8781, 8781, 8793, 8644, 8644, 
8713, 8644, 7470, 8713, 877, 7808, 7808, 8489, 8644, 6114, 6114, 
6114, 7298, 8311, 7290, 6443, 6743, 6114, 7565, 6129, 6129, 7565, 
885, 6888, 8786, 8786, 6559, 6114, 6060, 6559, 8650, 6730, 7946, 
7565, 986, 6651, 8268, 6114, 6338, 998, 8793, 8344, 8644, 6060, 
6338, 8644, 6559, 7290, 6577, 6443, 8713, 6443, 8713, 8020, 7996, 
6867, 8701, 8644, 859, 7565, 863, 940, 7306, 6311, 7565, 6693, 
854, 7422, 6684, 8850, 8834, 6888, 6443, 7290, 7474, 854, 8169, 
6313, 7442, 7717, 8596, 8713, 8121, 8489, 6792, 8311, 7565, 7565, 
7565, 7285, 6128, 6128, 8931, 7290, 7290, 8644, 8644, 8344, 8173, 
6059, 7565, 303, 6059, 8311, 7317, 854, 6284, 7317, 8020, 8311, 
8311, 8020, 6541, 859, 7211, 998, 854, 854, 8781, 6407, 6790, 
8311, 7317, 7470, 6114, 854, 7279, 8344, 303, 6255, 6255, 8223, 
8344, 8558, 7298, 7470, 986, 986, 986, 989, 8558, 6313, 7994, 
6443, 7813, 8558, 885, 6443, 7912, 8713, 7912, 877, 8311, 7098, 
6443, 6541, 8701, 8701, 7470, 7474, 908, 6577, 6128, 6255, 6128, 
8712, 8644, 6443, 8701, 8311, 7911, 8781, 7911, 8793, 7290, 8644, 
8713, 6443, 6559, 859, 7285, 7808, 8713, 8644, 6114, 6114, 6114, 
998, 8311, 8650, 6443, 8558, 6445, 6380, 854, 7565, 8850, 6730, 
6114, 7474, 7290, 7290, 7565, 6835, 6443, 8572, 7565, 986, 854, 
8713, 8558, 6338, 8644, 8644, 6060, 8793, 7290, 6577, 7290, 6559, 
6443, 8361, 854, 8713, 8020, 8099, 7635, 6835, 8644, 8425, 7061, 
7470, 8713, 7306, 854, 7565, 6255, 8211, 8850, 8873, 7474, 7290, 
7474, 6255, 854, 6023, 7442, 7717, 7442, 7990, 8121, 8489, 8558, 
7565, 7565, 854, 8768, 6393, 7290, 8644, 8644, 8644, 6389, 8173, 
6059, 7565, 8650, 6743, 6661, 852, 852, 8794, 8020, 6283, 6064, 
859, 998, 863, 854, 8781, 6407, 885, 6743, 7474, 7470, 7298, 
8169, 8220, 8344, 303, 6255, 8223, 8344, 8409, 7298, 7822, 986, 
986, 986, 986, 859, 6443, 7285, 7422, 7813, 6403, 8311, 8311, 
8713, 8713, 8425, 7061, 8311, 8311, 8644, 6407, 8701, 8701, 7470, 
908, 6577, 7565, 7298, 8712, 6443, 6443, 8701, 8305, 7911, 8781, 
8781, 8793, 8644, 6114, 6114, 6443, 859, 7470, 7808, 6150, 7994, 
6114, 7285, 6114, 6407, 8311, 7290, 6443, 7290, 6445, 6380, 7565, 
7939, 7290, 7290, 7474, 7474, 6728, 8701, 6443, 8177, 7565, 854, 
8713, 8558, 6338, 888, 8644, 6060, 6888, 7474, 8489, 6559, 6559, 
6443, 8216, 6443, 8713, 6284, 6403, 6283, 6835, 8644, 859, 7565, 
7565, 940, 8177, 7485, 7565, 8211, 6443, 7474, 6888, 7474, 7290, 
7474, 863, 854, 8931, 7682, 7717, 859, 6792, 8713, 8489, 8311, 
8425, 854, 8768, 6393, 7290, 8644, 7290, 8644, 6389, 8173, 6384, 
8664, 7994, 6661, 852, 8794, 8020, 8311, 8020, 859, 998, 863, 
854, 7946, 7285, 6443, 7474, 7470, 8220, 8169, 8344, 6255, 8223, 
7565, 8713, 7298, 8701, 986, 986, 986, 986, 7442, 6114, 6064, 
6403, 8311, 8311, 6443, 8713, 6790, 8713, 859, 7061, 7829, 6521, 
6888, 6888, 8701, 7470, 8644, 8644, 6255, 8712, 8644, 6443, 8305, 
7891, 8781, 8781, 7290, 6114, 6114, 6114, 877, 7994, 7808, 6684, 
7994, 6114, 859, 877, 6114, 8311, 7290, 7290, 7290, 6380), PREVDIA_cm = c(2.794, 
4.064, 5.08, 6.35, 27.178, 13.208, 20.828, 22.098, 25.908, 19.812, 
23.622, 12.7, 13.97, 36.83, 53.34, 17.018, 22.098, 23.114, 25.146, 
17.272, 36.576, 26.67, 27.686, 13.97, 4.572, 13.208, 14.478, 
5.842, 69.596, 28.956, 20.32, 20.574, 19.558, 23.876, 3.048, 
4.064, 32.512, 4.318, 3.048, 5.842, 3.048, 14.478, 12.446, 12.7, 
14.224, 16.764, 5.334, 2.794, 20.066, 7.112, 84.582, 41.402, 
32.004, 23.368, 15.24, 5.334, 3.302, 7.112, 13.208, 18.288, 19.05, 
36.068, 14.732, 13.97, 12.954, 31.242, 15.494, 12.7, 5.08, 16.51, 
4.064, 2.794, 18.796, 14.732, 5.334, 14.478, 3.302, 14.478, 45.72, 
16.256, 24.13, 36.576, 15.24, 17.526, 12.954, 14.986, 13.208, 
14.224, 17.78, 35.814, 20.32, 13.208, 13.462, 2.54, 13.208, 15.494, 
16.002, 6.096, 16.256, 17.78, 16.002, 28.956, 12.7, 18.796, 12.954, 
7.874, 2.54, 8.382, 13.97, 16.764, 2.794, 26.162, 13.716, 2.54, 
12.954, 20.32, 20.574, 14.478, 76.2, 3.302, 45.212, 27.94, 14.224, 
22.606, 12.446, 3.302, 2.794, 20.574, 22.606, 40.386, 54.102, 
30.988, 32.004, 3.81, 3.048, 2.794, 4.318, 4.064, 19.812, 13.716, 
17.526, 12.954, 13.97, 19.812, 15.748, 12.446, 16.764, 30.226, 
19.05, 17.78, 4.826, 32.258, 56.388, 15.494, 14.224, 13.716, 
3.81, 14.224, 15.494, 19.812, 45.466, 2.794, 18.542, 13.462, 
34.798, 16.51, 23.114, 20.828, 6.096, 14.478, 18.288, 4.064, 
22.86, 18.034, 17.018, 14.478, 3.302, 4.572, 4.826, 4.318, 15.24, 
12.7, 22.606, 23.114, 14.986, 20.066, 6.35, 17.78, 21.59, 27.178, 
13.208, 17.018, 19.812, 19.304, 17.526, 34.798, 15.748, 42.926, 
60.96, 5.08, 13.462, 5.08, 30.988, 30.226, 18.288, 14.986, 14.986, 
13.716, 3.048, 19.558, 6.858, 3.81, 6.604, 3.048, 14.986, 14.732, 
38.862, 16.51, 3.556, 16.51, 2.794, 15.748, 16.256, 14.732, 30.48, 
24.892, 7.62, 2.54, 2.794, 6.35, 18.542, 20.32, 45.466, 8.89, 
5.08, 2.794, 4.572, 25.146, 13.716, 4.318, 14.986, 2.54, 3.81, 
9.398, 26.67, 41.91, 24.892, 13.716, 19.05, 19.304, 31.496, 27.178, 
25.4, 22.86, 48.514, 27.432, 19.558, 30.988, 36.83, 5.08, 7.62, 
18.288, 22.352, 16.002, 18.796, 15.24, 16.764, 13.208, 6.096, 
18.542, 7.874, 2.54, 7.874, 34.29, 2.794, 2.794, 3.302, 2.794, 
14.478, 46.228, 31.75, 16.51, 23.876, 13.97, 16.51, 16.256, 3.81, 
66.294, 20.574, 18.034, 25.654, 54.61, 8.636, 3.81, 3.302, 4.826, 
4.826, 4.064, 13.208, 14.224, 17.018, 18.796, 17.272, 18.034, 
19.812, 15.494, 14.986, 12.7, 21.59, 33.274, 2.794, 17.018, 15.748, 
12.954, 3.81, 17.526, 3.556, 13.462, 17.526, 13.97, 17.272, 3.048, 
15.748, 15.494, 30.734, 26.924, 20.066, 6.096, 18.542, 3.048, 
13.462, 21.59, 13.716, 16.256, 2.54, 5.08, 4.318, 14.224, 20.066, 
18.288, 17.526, 26.924, 18.796, 20.32, 17.018, 14.478, 20.574, 
14.986, 30.226, 14.986, 6.096, 13.716, 14.224, 35.052, 16.256, 
38.1, 6.858, 7.62, 24.638, 17.78, 15.24, 13.208, 24.13, 32.512, 
16.764, 3.81, 4.318, 4.318, 18.796, 13.462, 45.466, 24.384, 2.54, 
15.24, 9.144, 17.018, 17.272, 35.814, 24.13, 13.462, 3.556, 3.81, 
5.08, 10.414, 19.304, 12.7, 13.97, 3.556, 4.064, 8.382, 2.794, 
14.986, 23.622, 5.842, 4.318, 3.556, 6.096, 38.354, 22.606, 20.32, 
20.574, 13.462, 20.828, 27.94, 29.464, 13.208, 12.7, 17.272, 
3.81, 18.796, 12.954, 32.258, 16.002, 3.302, 32.766, 12.7, 20.828, 
19.304, 24.892, 12.954, 22.098, 5.334, 14.478, 4.064, 4.064, 
20.574, 3.048, 3.302, 3.048, 19.558, 17.018, 16.256, 20.32, 14.478, 
14.478, 19.812, 17.526, 22.098, 55.118, 6.604, 12.446, 7.874, 
8.382, 2.54, 2.794, 3.556, 7.366, 14.224, 14.224, 32.766, 25.654, 
13.716, 18.288, 17.526, 37.338, 13.716, 20.828, 16.51, 14.986, 
15.748, 15.494, 21.59, 4.318, 14.224, 4.826, 16.002, 19.304, 
26.162, 28.194, 3.302, 14.224, 19.304, 6.096, 2.794, 19.304, 
2.794, 14.986, 13.462, 30.734, 2.794, 4.826, 2.794, 17.526, 20.574, 
16.51, 18.796, 16.51, 14.986, 12.7, 2.794, 14.478, 23.114, 20.574, 
23.876, 9.906, 18.034, 31.496, 18.034, 27.178, 7.62), ANN_DIA_GROWTH_cm = c(0.2032, 
0.2032, 0.2032, 0.2032, 0.635, 0.4826, 0.5842, 0.5842, 0.635, 
0.5842, 0.4826, 0.4064, 0.4826, 0.5588, 0.4572, 0.4826, 0.5842, 
0.635, 0.635, 0.4826, 0.5588, 0.635, 0.635, 0.4826, 0.2032, 0.4826, 
0.4826, 0.2032, 0.4826, 0.508, 0.5842, 0.5842, 0.5842, 0.635, 
0.2032, 0.2032, 0.508, 0.2032, 0.2032, 0.2032, 0.1524, 0.4826, 
0.4064, 0.4064, 0.4826, 0.3556, 0.2032, 0.2032, 0.5842, 0.2032, 
0.4572, 0.4572, 0.508, 0.635, 0.4826, 0.2032, 0.2032, 0.2032, 
0.4826, 0.5842, 0.5842, 0.5588, 0.4826, 0.4826, 0.3556, 0.508, 
0.3556, 0.3556, 0.2032, 0.4826, 0.2032, 0.2032, 0.4064, 0.4826, 
0.2032, 0.4826, 0.2032, 0.4826, 0.4318, 0.4826, 0.635, 0.2794, 
0.4826, 0.4826, 0.4826, 0.4826, 0.4826, 0.4826, 0.4826, 0.5588, 
0.5842, 0.4826, 0.4826, 0.2032, 0.4826, 0.4826, 0.4826, 0.2032, 
0.4826, 0.4826, 0.4826, 0.508, 0.4064, 0.5842, 0.4826, 0.4064, 
0.2032, 0.4064, 0.4826, 0.4826, 0.2032, 0.4826, 0.4826, 0.2032, 
0.4826, 0.5842, 0.5842, 0.4826, 0.4572, 0.1524, 0.4318, 0.4826, 
0.3556, 0.4064, 0.4064, 0.2032, 0.2032, 0.5842, 0.5842, 0.4572, 
0.4572, 0.4572, 0.508, 0.2032, 0.2032, 0.2032, 0.2032, 0.2032, 
0.5842, 0.4826, 0.4826, 0.4826, 0.3556, 0.4064, 0.3556, 0.3556, 
0.4826, 0.508, 0.5842, 0.4826, 0.2032, 0.508, 0.4826, 0.4826, 
0.4826, 0.4826, 0.2032, 0.3556, 0.4826, 0.5842, 0.4318, 0.2032, 
0.5842, 0.4826, 0.5588, 0.4826, 0.4826, 0.5842, 0.2032, 0.4826, 
0.5842, 0.2032, 0.5842, 0.5842, 0.4826, 0.4826, 0.2032, 0.2032, 
0.2032, 0.2032, 0.4826, 0.4064, 0.5842, 0.635, 0.4826, 0.4064, 
0.2032, 0.4826, 0.5842, 0.635, 0.4826, 0.4826, 0.5842, 0.4064, 
0.4826, 0.5588, 0.4826, 0.4572, 0.4572, 0.2032, 0.3556, 0.2032, 
0.508, 0.508, 0.5842, 0.4826, 0.4826, 0.4826, 0.2032, 0.5842, 
0.2032, 0.2032, 0.2032, 0.1524, 0.3556, 0.4826, 0.4572, 0.4826, 
0.2032, 0.4826, 0.2032, 0.4826, 0.4826, 0.4826, 0.508, 0.635, 
0.2032, 0.2032, 0.1524, 0.2032, 0.5842, 0.5842, 0.4318, 0.4064, 
0.2032, 0.2032, 0.2032, 0.635, 0.4826, 0.2032, 0.3556, 0.2032, 
0.2032, 0.4064, 0.635, 0.4572, 0.635, 0.4826, 0.5842, 0.5842, 
0.4572, 0.635, 0.635, 0.5842, 0.4572, 0.635, 0.5842, 0.508, 0.5588, 
0.2032, 0.2032, 0.4064, 0.5842, 0.4826, 0.5842, 0.4826, 0.4826, 
0.4826, 0.2032, 0.5842, 0.4064, 0.2032, 0.4064, 0.5588, 0.2032, 
0.1524, 0.1524, 0.2032, 0.4826, 0.4318, 0.508, 0.3556, 0.4826, 
0.3556, 0.3556, 0.4826, 0.2032, 0.4826, 0.5842, 0.5842, 0.635, 
0.4572, 0.4064, 0.2032, 0.2032, 0.2032, 0.2032, 0.2032, 0.4826, 
0.4826, 0.4826, 0.5842, 0.3556, 0.4064, 0.4064, 0.3556, 0.3556, 
0.4064, 0.5842, 0.5588, 0.2032, 0.4826, 0.4826, 0.4826, 0.2032, 
0.4826, 0.2032, 0.4826, 0.4826, 0.4826, 0.4826, 0.2032, 0.4826, 
0.4826, 0.508, 0.4826, 0.5842, 0.2032, 0.5842, 0.2032, 0.4826, 
0.5842, 0.4826, 0.4826, 0.2032, 0.2032, 0.2032, 0.4826, 0.5842, 
0.5842, 0.4826, 0.635, 0.4064, 0.5842, 0.4826, 0.4826, 0.5842, 
0.4826, 0.508, 0.4826, 0.2032, 0.4826, 0.4826, 0.5588, 0.4826, 
0.5588, 0.2032, 0.2032, 0.635, 0.4826, 0.4826, 0.4826, 0.635, 
0.508, 0.4826, 0.2032, 0.2032, 0.2032, 0.4064, 0.4826, 0.4318, 
0.635, 0.1524, 0.4826, 0.4064, 0.4826, 0.4826, 0.5588, 0.635, 
0.4826, 0.2032, 0.2032, 0.2032, 0.4064, 0.5842, 0.4064, 0.4826, 
0.2032, 0.2032, 0.3556, 0.2032, 0.4826, 0.4826, 0.2032, 0.2032, 
0.2032, 0.2032, 0.4572, 0.5842, 0.5842, 0.5842, 0.4826, 0.5842, 
0.4826, 0.4572, 0.4826, 0.4064, 0.4826, 0.1524, 0.5842, 0.4826, 
0.508, 0.4826, 0.2032, 0.4572, 0.4064, 0.5842, 0.5842, 0.635, 
0.4826, 0.5842, 0.2032, 0.4826, 0.2032, 0.2032, 0.5842, 0.2032, 
0.1524, 0.2032, 0.5842, 0.4826, 0.4826, 0.4064, 0.3556, 0.3556, 
0.4064, 0.4826, 0.5842, 0.4572, 0.2032, 0.4064, 0.4064, 0.4064, 
0.2032, 0.2032, 0.2032, 0.2032, 0.4826, 0.4826, 0.508, 0.4826, 
0.3556, 0.4064, 0.3556, 0.5588, 0.4826, 0.5842, 0.4826, 0.4826, 
0.4826, 0.4826, 0.5842, 0.2032, 0.4826, 0.1524, 0.4826, 0.5842, 
0.635, 0.508, 0.2032, 0.4826, 0.5842, 0.2032, 0.2032, 0.5842, 
0.2032, 0.4826, 0.4826, 0.508, 0.2032, 0.2032, 0.2032, 0.4826, 
0.5842, 0.4826, 0.5842, 0.3556, 0.4826, 0.4064, 0.2032, 0.4826, 
0.635, 0.4064, 0.4826, 0.4064, 0.5842, 0.508, 0.5842, 0.635, 
0.2032), HT_m = c(5.48646671543526, 5.18166300902219, 7.62009266032675, 
9.44891489880517, 14.6305779078274, 13.106559375762, 9.1441111923921, 
17.9834186783711, 1.82882223847842, 18.2882223847842, 8.22970007315289, 
9.44891489880517, 7.92489636673982, 7.92489636673982, 18.5930260911973, 
12.4969519629359, 16.4594001463058, 11.5825408436967, 8.83930748597903, 
15.8497927334796, 21.0314557425018, 21.641063155328, 11.8873445501097, 
11.8873445501097, 6.40087783467447, 9.1441111923921, 8.53450377956596, 
6.0960741282614, 11.5825408436967, 14.9353816142404, 11.5825408436967, 
11.8873445501097, 14.0209704950012, 10.0585223116313, 3.96244818336991, 
3.96244818336991, 12.4969519629359, 3.35284077054377, 3.35284077054377, 
9.44891489880517, 2.43842965130456, 8.83930748597903, 7.31528895391368, 
10.0585223116313, 2.13362594489149, 11.8873445501097, 4.26725188978298, 
3.0480370641307, 14.9353816142404, 7.92489636673982, 21.945866861741, 
23.1650816873933, 17.9834186783711, 16.4594001463058, 7.92489636673982, 
3.0480370641307, 4.26725188978298, 3.96244818336991, 7.31528895391368, 
14.0209704950012, 9.44891489880517, 20.1170446232626, 7.92489636673982, 
7.92489636673982, 11.5825408436967, 11.8873445501097, 10.3633260180444, 
7.92489636673982, 6.40087783467447, 6.0960741282614, 6.40087783467447, 
4.57205559619605, 6.0960741282614, 7.92489636673982, 3.0480370641307, 
6.40087783467447, 6.40087783467447, 8.53450377956596, 16.1545964398927, 
7.62009266032675, 14.0209704950012, 14.9353816142404, 7.92489636673982, 
10.9729334308705, 10.9729334308705, 6.0960741282614, 7.92489636673982, 
7.01048524750061, 10.3633260180444, 11.8873445501097, 11.8873445501097, 
3.0480370641307, 10.0585223116313, 5.48646671543526, 7.92489636673982, 
11.8873445501097, 7.62009266032675, 3.96244818336991, 10.9729334308705, 
8.53450377956596, 10.0585223116313, 14.9353816142404, 10.6681297244574, 
9.44891489880517, 4.57205559619605, 7.01048524750061, 3.96244818336991, 
6.0960741282614, 7.31528895391368, 6.40087783467447, 3.0480370641307, 
9.1441111923921, 9.44891489880517, 3.0480370641307, 9.44891489880517, 
7.01048524750061, 7.92489636673982, 10.6681297244574, 18.5930260911973, 
3.96244818336991, 13.106559375762, 7.01048524750061, 7.92489636673982, 
10.0585223116313, 11.2777371372836, 3.96244818336991, 6.40087783467447, 
5.79127042184833, 2.13362594489149, 10.3633260180444, 12.4969519629359, 
9.44891489880517, 8.53450377956596, 3.0480370641307, 2.74323335771763, 
5.48646671543526, 4.57205559619605, 4.26725188978298, 6.0960741282614, 
8.22970007315289, 9.44891489880517, 20.1170446232626, 7.01048524750061, 
9.75371860521824, 9.44891489880517, 10.9729334308705, 10.3633260180444, 
15.5449890270666, 11.5825408436967, 16.4594001463058, 6.0960741282614, 
13.106559375762, 12.1921482565228, 14.3257742014143, 9.44891489880517, 
11.2777371372836, 5.48646671543526, 10.0585223116313, 4.57205559619605, 
10.6681297244574, 10.0585223116313, 3.0480370641307, 6.0960741282614, 
7.92489636673982, 7.92489636673982, 8.83930748597903, 11.5825408436967, 
8.22970007315289, 3.96244818336991, 7.01048524750061, 5.48646671543526, 
4.57205559619605, 16.4594001463058, 14.0209704950012, 10.9729334308705, 
8.53450377956596, 4.87685930260912, 4.87685930260912, 8.22970007315289, 
3.96244818336991, 10.3633260180444, 12.4969519629359, 9.44891489880517, 
17.9834186783711, 11.8873445501097, 14.9353816142404, 7.92489636673982, 
10.9729334308705, 11.2777371372836, 17.9834186783711, 12.4969519629359, 
14.6305779078274, 11.2777371372836, 8.83930748597903, 6.0960741282614, 
17.9834186783711, 20.1170446232626, 19.2026335040234, 21.0314557425018, 
6.40087783467447, 5.48646671543526, 7.01048524750061, 12.4969519629359, 
18.2882223847842, 9.44891489880517, 11.8873445501097, 11.8873445501097, 
8.53450377956596, 4.57205559619605, 9.44891489880517, 5.79127042184833, 
4.26725188978298, 9.44891489880517, 2.13362594489149, 7.62009266032675, 
7.31528895391368, 10.0585223116313, 2.13362594489149, 3.0480370641307, 
4.87685930260912, 3.0480370641307, 13.7161667885881, 10.3633260180444, 
8.53450377956596, 7.62009266032675, 20.1170446232626, 3.0480370641307, 
3.96244818336991, 3.0480370641307, 4.87685930260912, 14.9353816142404, 
8.53450377956596, 20.1170446232626, 4.87685930260912, 4.87685930260912, 
4.57205559619605, 6.40087783467447, 15.5449890270666, 7.92489636673982, 
6.40087783467447, 7.01048524750061, 3.96244818336991, 3.96244818336991, 
5.48646671543526, 10.0585223116313, 10.9729334308705, 16.4594001463058, 
7.62009266032675, 12.8017556693489, 8.22970007315289, 10.6681297244574, 
7.92489636673982, 13.4113630821751, 9.1441111923921, 14.0209704950012, 
10.9729334308705, 10.9729334308705, 6.40087783467447, 17.0690075591319, 
7.31528895391368, 7.92489636673982, 13.4113630821751, 10.9729334308705, 
10.0585223116313, 9.44891489880517, 10.0585223116313, 14.9353816142404, 
8.53450377956596, 4.87685930260912, 4.87685930260912, 7.92489636673982, 
3.96244818336991, 6.0960741282614, 11.8873445501097, 3.96244818336991, 
4.87685930260912, 6.70568154108754, 4.26725188978298, 9.44891489880517, 
14.9353816142404, 11.8873445501097, 10.9729334308705, 7.01048524750061, 
8.22970007315289, 9.44891489880517, 11.5825408436967, 3.96244818336991, 
17.0690075591319, 13.106559375762, 7.31528895391368, 7.01048524750061, 
14.0209704950012, 6.40087783467447, 3.0480370641307, 3.35284077054377, 
3.0480370641307, 4.87685930260912, 4.26725188978298, 7.92489636673982, 
4.87685930260912, 9.44891489880517, 7.31528895391368, 4.57205559619605, 
9.75371860521824, 10.0585223116313, 6.40087783467447, 10.9729334308705, 
12.4969519629359, 17.0690075591319, 13.106559375762, 4.57205559619605, 
17.6786149719581, 4.57205559619605, 4.26725188978298, 5.79127042184833, 
12.1921482565228, 5.18166300902219, 12.1921482565228, 7.62009266032675, 
3.35284077054377, 7.92489636673982, 4.87685930260912, 3.96244818336991, 
7.92489636673982, 7.92489636673982, 13.106559375762, 9.1441111923921, 
7.01048524750061, 13.106559375762, 4.87685930260912, 9.1441111923921, 
12.4969519629359, 10.9729334308705, 10.0585223116313, 3.96244818336991, 
4.87685930260912, 5.18166300902219, 10.6681297244574, 6.0960741282614, 
10.0585223116313, 10.9729334308705, 17.9834186783711, 10.3633260180444, 
19.5074372104365, 11.2777371372836, 14.0209704950012, 12.1921482565228, 
12.8017556693489, 18.8978297976103, 14.0209704950012, 6.0960741282614, 
7.92489636673982, 15.5449890270666, 22.2506705681541, 13.4113630821751, 
14.6305779078274, 6.0960741282614, 5.79127042184833, 16.1545964398927, 
7.92489636673982, 7.62009266032675, 11.5825408436967, 14.9353816142404, 
15.8497927334796, 7.01048524750061, 4.57205559619605, 4.26725188978298, 
9.44891489880517, 7.92489636673982, 11.2777371372836, 13.4113630821751, 
2.13362594489149, 3.0480370641307, 7.92489636673982, 9.1441111923921, 
16.4594001463058, 13.106559375762, 17.9834186783711, 21.945866861741, 
17.9834186783711, 2.13362594489149, 4.26725188978298, 3.0480370641307, 
7.92489636673982, 10.3633260180444, 7.92489636673982, 9.44891489880517, 
5.79127042184833, 4.26725188978298, 9.44891489880517, 6.40087783467447, 
13.106559375762, 11.2777371372836, 6.0960741282614, 3.65764447695684, 
6.0960741282614, 3.35284077054377, 16.1545964398927, 16.4594001463058, 
10.9729334308705, 15.2401853206535, 9.1441111923921, 8.53450377956596, 
9.75371860521824, 10.6681297244574, 9.1441111923921, 7.31528895391368, 
7.92489636673982, 8.53450377956596, 10.0585223116313, 10.3633260180444, 
8.53450377956596, 3.65764447695684, 5.48646671543526, 14.6305779078274, 
9.1441111923921, 10.3633260180444, 6.40087783467447, 11.2777371372836, 
8.22970007315289, 11.8873445501097, 4.87685930260912, 4.87685930260912, 
7.01048524750061, 3.0480370641307, 10.3633260180444, 3.35284077054377, 
5.79127042184833, 4.26725188978298, 9.1441111923921, 9.44891489880517, 
14.0209704950012, 11.2777371372836, 3.96244818336991, 8.53450377956596, 
7.92489636673982, 11.2777371372836, 9.1441111923921, 18.8978297976103, 
11.5825408436967, 9.1441111923921, 4.87685930260912, 6.40087783467447, 
4.26725188978298, 5.18166300902219, 4.26725188978298, 5.79127042184833, 
7.92489636673982, 9.44891489880517, 8.53450377956596, 8.22970007315289, 
6.40087783467447, 9.44891489880517, 13.4113630821751, 16.4594001463058, 
10.9729334308705, 13.106559375762, 11.8873445501097, 5.48646671543526, 
4.57205559619605, 0.91441111923921, 8.53450377956596, 6.40087783467447, 
14.0209704950012, 6.40087783467447, 13.106559375762, 13.7161667885881, 
16.4594001463058, 11.2777371372836, 6.0960741282614, 6.0960741282614, 
7.92489636673982, 2.13362594489149, 2.13362594489149, 11.8873445501097, 
3.96244818336991, 12.1921482565228, 12.4969519629359, 14.0209704950012, 
3.96244818336991, 6.0960741282614, 4.87685930260912, 9.44891489880517, 
10.0585223116313, 7.62009266032675, 10.6681297244574, 9.44891489880517, 
10.3633260180444, 13.106559375762, 3.0480370641307, 11.8873445501097, 
17.373811265545, 6.70568154108754, 14.0209704950012, 7.62009266032675, 
11.5825408436967, 14.9353816142404, 13.4113630821751, 3.96244818336991, 
5.48646671543526)), row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 
21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 
34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 
47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 
60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 
73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 
86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 
99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 
110L, 111L, 112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 
121L, 122L, 123L, 124L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 
132L, 133L, 134L, 135L, 136L, 137L, 138L, 139L, 140L, 141L, 142L, 
143L, 144L, 145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 
154L, 155L, 156L, 157L, 158L, 159L, 160L, 161L, 162L, 163L, 164L, 
165L, 166L, 167L, 168L, 169L, 170L, 171L, 172L, 173L, 174L, 175L, 
176L, 177L, 178L, 179L, 180L, 181L, 182L, 183L, 184L, 185L, 186L, 
187L, 188L, 189L, 190L, 191L, 192L, 193L, 194L, 195L, 196L, 197L, 
198L, 199L, 200L, 201L, 202L, 203L, 204L, 205L, 206L, 207L, 208L, 
209L, 210L, 211L, 212L, 213L, 214L, 215L, 216L, 217L, 218L, 220L, 
221L, 222L, 223L, 224L, 225L, 226L, 227L, 228L, 229L, 230L, 231L, 
232L, 233L, 234L, 235L, 236L, 237L, 238L, 239L, 240L, 241L, 242L, 
243L, 244L, 245L, 246L, 247L, 248L, 249L, 250L, 251L, 252L, 253L, 
254L, 255L, 256L, 257L, 258L, 259L, 260L, 261L, 262L, 263L, 264L, 
265L, 266L, 267L, 268L, 269L, 270L, 271L, 272L, 273L, 274L, 275L, 
276L, 277L, 278L, 279L, 280L, 281L, 282L, 283L, 284L, 285L, 286L, 
287L, 288L, 289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 297L, 
298L, 299L, 300L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L, 
309L, 310L, 311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L, 319L, 
320L, 321L, 322L, 323L, 324L, 325L, 326L, 327L, 328L, 329L, 330L, 
331L, 332L, 333L, 334L, 335L, 336L, 337L, 338L, 339L, 340L, 341L, 
342L, 343L, 344L, 345L, 346L, 347L, 348L, 349L, 350L, 351L, 352L, 
353L, 354L, 355L, 356L, 357L, 358L, 359L, 360L, 361L, 362L, 363L, 
364L, 365L, 366L, 367L, 368L, 369L, 370L, 371L, 372L, 373L, 375L, 
376L, 377L, 378L, 379L, 380L, 381L, 382L, 383L, 384L, 385L, 386L, 
387L, 388L, 389L, 390L, 391L, 392L, 393L, 394L, 395L, 396L, 397L, 
398L, 399L, 400L, 401L, 402L, 403L, 404L, 405L, 406L, 407L, 408L, 
409L, 410L, 411L, 412L, 413L, 414L, 415L, 416L, 417L, 418L, 419L, 
420L, 421L, 422L, 423L, 424L, 425L, 426L, 427L, 428L, 429L, 430L, 
432L, 433L, 434L, 435L, 436L, 437L, 438L, 439L, 440L, 441L, 442L, 
443L, 444L, 445L, 446L, 447L, 448L, 449L, 450L, 451L, 452L, 453L, 
454L, 455L, 456L, 457L, 458L, 459L, 460L, 461L, 462L, 463L, 464L, 
465L, 466L, 467L, 468L, 469L, 470L, 471L, 472L, 473L, 474L, 475L, 
476L, 477L, 478L, 479L, 480L, 481L, 482L, 483L, 484L, 485L, 486L, 
487L, 488L, 489L, 490L, 491L, 492L, 493L, 494L, 495L, 496L, 497L, 
498L, 499L, 500L, 501L, 502L, 503L), class = "data.frame")

## make data list 

jags.data <- list(y = ds$STATUSCD, 
                  PREVDIA_cm = ds$PREVDIA_cm, 
                  ANN_DIA_GROWTH_cm = ds$ANN_DIA_GROWTH_cm, 
                  HT_m = ds$HT_m,
                  sp = ds$SPCD,
                  Nsp = length(unique(ds$SPCD)), 
                  N = length(ds$TREE)
                  )

这是我在 R 中调用/运行模型的方式

library(R2jags)

# parameters to monitor
par.list <- c("p", "b0", "b1", "b2", "b3", "b4")

## Run model in R2Jags with parallel computing
survival_species.jags = jags.parallel(
  data = jags.data,
  model.file = "JAGS_survival_species.txt", 
  parameters.to.save = par.list,
  jags.seed = 123, n.chains = 3, n.iter = 9999, n.thin = 20,  
)

我怀疑这与物种、观察和索引的嵌套循环有关。我是 jag/bug 代码的新手，因此非常感谢任何帮助。感谢您的宝贵时间。

我可以运行更简单的模型（没有物种协同效应）。这是 j 循环让我搞砸了。

Answer 1

正如回答问题的评论所建议的，我认为这里的问题确实与索引有关。简而言之，您将格式化为向量的观察结果 (

) 传递给试图将它们视为矩阵的模型（在您的可能性中为

y[i,j]

）。有两种选择：（1）重新格式化数据，使其位于矩阵中；（2）重写模型，以便可以向其传递观察向量。我将在这里采用第二种方法，从您粘贴的

ds

对象开始。

第一件事是为您的群体（在本例中为物种）建立索引，以便 JAGS 知道会发生什么。例如，您可以通过创建一个参考数据框来为每个物种分配一个唯一的 ID（从 1:（物种数）开始）来实现此目的。然后将该参考数据框加入到您的原始数据中 (

ds

)。现在每个物种都被分配了一个唯一的索引。是的，该物种已经被唯一标识，但我为它们重新分配新 ID 的原因将在下面揭晓。

library(tidyverse)
referenceDF <- data.frame(sp=unique(ds$SPCD),id=1:length(unique(ds$SPCD))) 
ds <- ds %>% 
  left_join(referenceDF, by = c("SPCD" = "sp") )

接下来，制作数据列表。您将使用我们上面创建的 ID，而不是为物种分配其代码。另请注意，您需要设置

N = nrow(ds)

以确保您拥有正确数量的观察值。

jags.data <- list(y = ds$STATUSCD, 
                  PREVDIA_cm = ds$PREVDIA_cm, 
                  ANN_DIA_GROWTH_cm = ds$ANN_DIA_GROWTH_cm, 
                  HT_m = ds$HT_m,
                  sp = ds$id,
                  Nsp = length(unique(ds$SPCD)), 
                  N = nrow(ds)
)

考虑到数据的新设置，让我们重写模型。完整的代码如下，但这里是重点。首先，我将使用嵌套索引。我们的 for 循环很可能会遍历每个观察结果。对于生态模型中的每个观察，我通过编写

b0

来调用特定于物种的参数，例如

b0[sp[i]]

。这意味着，对于观察

，获取物种 ID（我将其设置为唯一的数字！），然后获取由该物种 ID 标识的参数。其次，这个方程预测了

p[i]

（每次观察）的值，我将其插入到

y[i]

的观察模型中（同样，每次观察）。第三，我为先验编写了一个单独的 for 循环，并按物种单独索引。例如，在修改模型时，我为每个

b0

分配了一个唯一的先验。我没有对超先验进行任何更改。

j in 1:nSp

总之，为了让您的模型运行，我（1）重新索引了物种，（2）修改了数据列表，（3）修改了模型以利用新的索引。有关 JAGS 中嵌套索引的更多信息，我推荐

https://masonfidino.com/nested_indexing/

。这是我使用 R2jags 和 rjags 运行的 - 我希望它对你有用！

Rjags 编译错误尺寸不匹配

问题描述投票：0回答：1

1个回答

最新问题

Rjags 编译错误尺寸不匹配

问题描述 投票：0回答：1

1个回答

最新问题

问题描述投票：0回答：1