如何通过迭代R中的列名来对rJAGS MCMC后验分布进行子集化？

Question

这是我的MCMC示例的快照：

尽管以samples[,1:15]的形式逐列进行子集化是很直观的，但显然我想从对列号的硬编码转换为公式化子集。

例如，这是我（成功地）通过beta子集的方式：

p <- ncol(X.mod) # p=8   
head(samples[, c(paste("beta[", 1:p, "]", sep = "")])

问题是，我无法弄清楚如何通过迭代列名来以公式化方式对这些样本进行子集化，这与我的y后验分布相关：

当我尝试通过n和p进行子集化时，会发生以下情况：

n <- nrow(X.mod) # n=52
p <- ncol(X.mod) # p=8
head(samples[, c(paste("y[",1:n,",", 1:p, "]", sep = ""))])

该子集无法选择所有y，因为1:n不会重复1:p。

如何为y[1:n,1:p]后验分布的所有子集？

样本数据：

samples=list(structure(c(-51.2677209544157, -21.4563066467399, 16.8163390467341, 
9.4403233375381, 48.1649529600012, 527.042041706746, 512.571280385213, 
573.056966431797, 492.87177606163, 515.43937748028, 1341.16877015021, 
1314.46850289829, 1299.28259509269, 1301.53294554643, 1320.78264289766, 
299.286629146479, 301.909535290067, 300.894814624028, 300.804302607962, 
300.232964708285, -3006.34967221901, -2874.20964445009, -2788.20702516807, 
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91.0541633678037, 90.9102211374358, 91.1560822802519, 91.0031643433501, 
-20.5391638580293, -20.598494387781, -20.6003012597676, -20.6303435292573, 
-20.6369790962729, 586.880362343332, 580.677805863983, 573.044264526859, 
574.309536298313, 567.446409074497, -121.00760356184, -120.443670943994, 
-119.403902369317, -120.025713139514, -120.12086457878, 262.761481825014, 
262.8571924679, 263.091693357767, 263.636726737316, 263.836394193792, 
2.99998007884072, 2.99942379397774, 2.99994292246781, 2.99999437834094, 
2.99999393092779, 43684833.8709732, 43853657.9085946, 43965230.3484224, 
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2.28031148982903e-08, 2.27452464612387e-08, 2.27718314881392e-08, 
2.27748253037098e-08, 51147.5432500239, 52617.8839201446, 52387.1302975914, 
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    "beta[4]", "beta[5]", "beta[6]", "beta[7]", "beta[8]", "phi", 
    "sigma.sq", "sigma.sq.w", "tau.sq", "w[1]", "w[2]", "w[3]", 
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    "y[29,3]"))))