Вот снимок моих образцов MCMC:
, хотя он интуитивно понятен для поднабора по столбцам в виде samples[,1:15]
, очевидно, я хотел бы сдвинутьот жесткого кодирования номеров столбцов до формульного поднабора.
Например, вот как я (успешно) подмножество бета-версий:
p <- ncol(X.mod) # p=8
head(samples[, c(paste("beta[", 1:p, "]", sep = "")])
Проблема в том, что я не могу понять, как подмножество этих выборок в формальной форме путем итерации столбцаИмена, которые релевантны для моих y
апостериорных распределений:
Вот что происходит, когда я пытаюсь установить подмножество n
и p
:
n <- nrow(X.mod) # n=52
p <- ncol(X.mod) # p=8
head(samples[, c(paste("y[",1:n,",", 1:p, "]", sep = ""))])
Подмножеству не удается выбрать все y
, поскольку 1:n
не повторяется для 1:p
.
Как мне установить подмножество для всех из y[1:n,1:p]
апостериорных распределений?
Пример данных:
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,
-2769.57351439289, -2841.15094775797, 18978.8438818469, 18861.3329448127,
18835.2759211416, 18843.9480121326, 19006.8849778275, 90.8125367572606,
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,
43913903.0394132, 43908130.4319428, 26293534.6902094, 26383613.17045,
26147749.137356, 26098414.0977608, 26280692.1742495, 2.28912396222813e-08,
2.28031148982903e-08, 2.27452464612387e-08, 2.27718314881392e-08,
2.27748253037098e-08, 51147.5432500239, 52617.8839201446, 52387.1302975914,
51694.3819485642, 52661.5824788161, 8288.63042107145, 7271.35048802946,
8004.90224346885, 4927.79219294683, 6213.91939841326, -121910.191472484,
-122362.741428785, -124110.51332543, -120733.292837535, -121831.210377512,
230071.066478833, 230287.794814824, 230860.030232403, 228148.880125279,
230333.173973695, 58966.85989857, 58290.5265589913, 58966.2214960444,
59519.8070715974, 58802.1396637729, 158277.070604939, 158278.084243585,
159558.969341073, 158206.366529875, 159426.208472455, -34631.8355987461,
-34609.6845179111, -35917.7360955642, -35814.2800339074, -36978.4911829625,
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63832.4336294562, 60989.0636476163, 63079.6258807178, -16093.0306896024,
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4740.84679297971, 5553.23308406456, 4646.47350755076, 5203.83240565698,
3836.21264149301, -42452.3446436508, -44176.1773649656, -44254.4042803305,
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19286.7821182529, 15618.4910885203, 17440.5647607157, 18530.2743457382,
694380.200995391, 696718.995471421, 693905.474727437, 695063.192208464,
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-38063.2925580272, -39235.2603601708, -38927.2812579938, -463.298832842201,
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-39913.5482978342, -39620.7226918087, -40950.5478134214, -40039.0598099734,
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-87487.5243492138, -88535.0891267321, -87215.625811017, -40395.9008156264,
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-47633.8104654962, -45788.0300150143, -6733.68790270814, -8175.62499754323,
-6656.38624378975, -7933.87717601099, -8826.27342533908, -24296.8117513574,
-21040.1429957975, -22854.3352422732, -24540.3392066565, -22262.6674224603,
36368.7050027012, 35771.2638538132, 37582.6249503995, 37474.0672148882,
34786.309716829, 61238.0631051517, 61395.3553743695, 62595.9115888391,
62409.4707276882, 61469.3534951057, -8946.0324795431, -8446.70860487308,
-9544.72651309003, -8679.57342708674, -9576.25960931779, -85699.6074359973,
-85155.9899379678, -85845.0121999715, -85085.0799491324, -83116.5520568948,
-69475.3035748836, -71336.8481369083, -69854.4490875094, -68279.0163230788,
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1461, 1461, 1461, 6319, 6319, 6319, 6319, 6319, 472, 472, 472,
472, 472, 20443, 20443, 20443, 20443, 20443, 168310, 168310,
168310, 168310, 168310, 44013, 44013, 44013, 44013, 44013, 1120,
1120, 1120, 1120, 1120, 1772, 1772, 1772, 1772, 1772, 476631,
476631, 476631, 476631, 476631, 12789, 12789, 12789, 12789, 12789,
21351, 21351, 21351, 21351, 21351, 414038, 414038, 414038, 414038,
414038, 79148, 79148, 79148, 79148, 79148, 301104, 301104, 301104,
301104, 301104, 2962, 2962, 2962, 2962, 2962, 723272, 723272,
723272, 723272, 723272, 390602, 390602, 390602, 390602, 390602,
486495, 486495, 486495, 486495, 486495, 8846, 8846, 8846, 8846,
8846, 199212, 199212, 199212, 199212, 199212, 70980, 70980, 70980,
70980, 70980, 71552, 71552, 71552, 71552, 71552, 34019, 34019,
34019, 34019, 34019, 1713, 1713, 1713, 1713, 1713, 66, 66, 66,
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17939, 17939, 17939, 17939, 17939, 14969, 14969, 14969, 14969,
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91818, 2833, 2833, 2833, 2833, 2833), .Dim = c(5L, 200L), .Dimnames = list(
NULL, c("b_0", "b_1", "b_2", "beta[1]", "beta[2]", "beta[3]",
"beta[4]", "beta[5]", "beta[6]", "beta[7]", "beta[8]", "phi",
"sigma.sq", "sigma.sq.w", "tau.sq", "w[1]", "w[2]", "w[3]",
"w[4]", "w[5]", "w[6]", "w[7]", "w[8]", "w[9]", "w[10]",
"w[11]", "w[12]", "w[13]", "w[14]", "w[15]", "w[16]", "w[17]",
"w[18]", "w[19]", "w[20]", "w[21]", "w[22]", "w[23]", "w[24]",
"w[25]", "w[26]", "w[27]", "w[28]", "w[29]", "w[30]", "w[31]",
"w[32]", "w[33]", "w[34]", "w[35]", "w[36]", "w[37]", "w[38]",
"w[39]", "w[40]", "w[41]", "w[42]", "w[43]", "w[44]", "w[45]",
"w[46]", "w[47]", "w[48]", "w[49]", "w[50]", "w[51]", "w[52]",
"y[1,1]", "y[2,1]", "y[3,1]", "y[4,1]", "y[5,1]", "y[6,1]",
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"y[29,3]"))))