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historical_data.R
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historical_data.R
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fJan <- c(
816, 1884, 1039, 340, 1919, 784, 340, 1310, 2084, 1174,
1868, 784, 843, 1682, 1151, 3006, 1598, 1127, 160, 568,
658, 240, 857, 368, 1082, 101, 736, 1546, 110, 155,
854
)
fFeb <- c(
2394, 2558, 2497, 453, 1908, 607, 2218, 2029, 347, 575,
792, 1213, 1406, 1341, 1533, 3393, 480, 1579, 473, 210,
2131, 961, 636, 343, 586, 221, 298, 2200, 237, 275,
980
)
fMar <- c(
3144, 3177, 386, 1120, 2274, 259, 3239, 1079, 1728, 978,
3718, 2704, 1187, 1300, 1089, 4393, 919, 941, 1986, 333,
2953, 403, 1463, 103, 1023, 887, 2357, 835, 621, 913,
494
)
fApr <- c(
2366, 1981, 87, 134, 1776, 400, 1743, 1409, 529, 497,
2403, 508, 102, 864, 1712, 959, 859, 1372, 799, 159,
2923, 479, 589, 324, 1060, 1114, 542, 185, 404, 125,
614
)
fMay <- c(
1499, 1079, 248, 149, 305, 229, 1457, 1565, 219, 148,
321, 115, 156, 837, 376, 373, 214, 441, 121, -11,
1617, 289, 135, 131, 137, 223, 197, 1060, 342, 348,
995
)
fJun <- c(
357, 221, -4, -52, 103, 48, 723, 195, 62, 325,
20, 55, 1935, 230, 371, 114, 110, 281, 332, -66,
973, 67, 141, 1259, 47, 81, 638, 130, -19, 25,
1348
)
fJul <- c(
71, 1006, 103, 24, 31, 11, 981, 57, 59, 198,
0, 201, 496, 164, 273, 28, 34, 630, 326, -3,
882, 179, 36, 516, -25, 174, 30, 40, -8, 50,
1262
)
fAug <- c(
59, 424, 566, 709, -35, -3, 1151, 163, 25, 119,
-16, 136, 153, 402, -47, 31, 201, 455, 247, 56,
823, 995, 17, 16, -46, 252, 26, 30, -15, 141,
268
)
fSep <- c(
-35, 25, 101, -21, 194, 85, 239, -53, 146, 72,
5, -19, 13, 4153, 37, 80, 5421, 279, 82, 99,
646, 535, -56, 294, -44, 1930, 117, 174, 107, 465,
12
)
fOct <- c(
98, 76, 31, -38, -6, 172, 904, 501, 18, 136,
28, 190, 1178, 819, 47, 37, 607, -9, -7, 1814,
189, 183, 37, 179, 86, 66, 17, 78, 41, 57,
5
)
fNov <- c(
331, 53, 2565, 63, 79, 558, 622, 140, 36, 747,
136, 83, 1295, 597, 285, 57, 296, 91, 4, 1026,
268, 585, 132, 2360, 1, 230, 1787, 18, 195, 1,
86
)
fDec <- c(
1757, 339, 742, 610, 241, 148, 1247, 613, 123, 724,
398, 58, 700, 1331, 312, 278, 419, 148, 74, 1965,
1092, 707, 688, 630, 186, 990, 2768, 107, 245, 250,
1000
)
# pJan <- c(
# 2.03, 4.64, 4.61, 1.32, 5.88, 3.35, 1.70, 3.93, 5.15, 4.84,
# 5.13, 3.99, 4.25, 3.83, 3.56, 7.91, 5.51, 2.48, 1.98, 4.29,
# 2.13, 1.20, 2.87, 2.67, 2.13, 1.52, 3.21, 2.99, 0.78, 1.58,
# 4.00
# )
#
# pFeb <- c(
# 5.09, 5.20, 5.37, 1.87, 4.23, 2.24, 5.91, 4.32, 1.31, 2.45,
# 2.66, 3.31, 3.82, 2.33, 2.89, 5.13, 1.90, 2.56, 2.91, 1.02,
# 4.77, 1.99, 1.91, 1.84, 2.11, 3.26, 1.54, 2.79, 1.72, 1.94,
# 3.82
# )
#
# pMar <- c(
# 7.49, 7.66, 1.39, 2.98, 4.54, 2.09, 7.06, 4.17, 5.94, 3.77,
# 7.57, 6.90, 3.13, 4.10, 1.92, 8.37, 3.00, 3.20, 6.28, 3.01,
# 6.71, 1.54, 4.34, 0.84, 3.41, 4.81, 6.30, 2.71, 5.37, 3.34,
# 2.22
# )
#
# pApr <- c(
# 4.49, 4.48, 0.46, 1.10, 5.46, 3.48, 5.61, 4.42, 2.63, 2.40,
# 4.99, 2.57, 1.18, 3.63, 5.65, 3.74, 4.87, 5.66, 2.60, 1.57,
# 6.29, 2.32, 0.74, 3.79, 3.54, 5.82, 1.98, 1.06, 2.90, 2.73,
# 3.75
# )
#
# pMay <- c(
# 6.44, 6.02, 4.79, 2.73, 3.08, 4.97, 4.42, 6.95, 2.72, 3.23,
# 4.32, 2.22, 3.66, 5.03, 1.38, 3.95, 1.22, 3.18, 3.12, 2.02,
# 5.47, 3.48, 3.52, 2.87, 2.70, 2.92, 3.93, 7.08, 4.37, 3.58,
# 4.65
# )
#
# pJun <- c(
# 2.67, 2.04, 2.23, 0.84, 2.48, 2.43, 6.62, 1.14, 2.03, 4.67,
# 1.65, 2.70, 11.0, 1.89, 3.63, 2.36, 3.28, 3.82, 4.59, 2.32,
# 3.15, 3.65, 2.66, 7.20, 4.28, 3.73, 6.29, 2.46, 2.81, 2.08,
# 7.62
# )
#
# pJul <- c(
# 1.67, 9.82, 4.68, 4.20, 2.58, 3.23, 7.30, 3.67, 5.35, 3.98,
# 3.22, 5.66, 3.97, 3.50, 4.26, 2.83, 3.28, 5.34, 6.46, 2.87,
# 6.48, 4.68, 2.44, 4.37, 2.56, 3.17, 1.94, 4.07, 3.43, 3.87,
# 4.77
# )
#
# pAug <- c(
# 2.25, 2.12, 6.39, 6.99, 2.71, 4.12, 6.30, 4.67, 3.13, 4.19,
# 2.20, 3.91, 3.23, 5.28, 1.31, 3.07, 3.48, 4.78, 2.71, 5.18,
# 4.28, 8.72, 2.15, 2.83, 1.47, 6.60, 3.43, 3.20, 4.08, 5.71,
# 2.33
# )
#
# pSep <- c(
# 7.25, 0.55, 0.33, 0.53, 5.83, 4.79, 3.96, 0.46, 4.96, 2.35,
# 2.68, 1.49, 1.73,13.24, 3.77, 3.82, 17.8, 4.42, 2.33, 3.95,
# 5.77, 3.95, 0.76, 5.50, 0.92, 8.02, 3.64, 4.75, 6.02, 7.51,
# 2.49
# )
#
# pOct <- c(
# 4.48, 2.93, 2.85, 2.00, 2.65, 4.14, 4.91, 8.16, 1.93, 4.54,
# 3.27, 3.65, 8.27, 2.91, 2.67, 2.99, 2.67, 0.08, 1.41, 7.96,
# 2.87, 1.76, 2.77, 3.68, 4.55, 0.85, 2.18, 2.49, 2.55, 2.80,
# 2.69
# )
#
# pNov <- c(
# 4.80, 1.35, 9.97, 3.26, 2.48, 3.85, 3.09, 2.08, 0.98, 5.08,
# 3.60, 2.38, 4.77, 3.32, 3.66, 2.19, 1.59, 2.03, 0.49, 3.38,
# 2.18, 3.25, 4.39, 7.53, 0.58, 3.31, 8.49, 1.05, 4.27, 0.43,
# 2.77
# )
#
# pDec <- c(
# 6.47, 2.67, 1.39, 4.10, 3.86, 0.76, 3.12, 3.78, 2.73, 2.84,
# 3.69, 2.38, 1.84, 3.82, 2.66, 4.75, 1.74, 1.85, 1.92, 3.32,
# 4.12, 2.11, 4.98, 3.42, 3.98, 4.12, 8.13, 2.77, 2.54, 3.43,
# 4.75
# )
#
# eJan <- c(
# 0.97, 5.52, 3.84, 0.54,11.23, 2.03, 0.67, 0.00, 0.00, 3.84,
# 2.03, 3.18, 0.00, 4.52, 0.00, 0.85, 2.32, 4.52, 1.22, 4.83,
# 1.80, 0.92, 2.31, 3.18, 2.44, 0.85, 2.32, 3.82, 1.15, 2.04,
# 2.65
# )
#
# eFeb <- c(
# 3.75, 4.64, 3.34, 0.03, 4.98, 2.50, 0.59, 0.10, 0.00, 3.34,
# 2.50, 2.54, 0.10, 1.92, 0.00, 2.41, 1.46, 1.92, 1.87, 1.21,
# 4.29, 2.76, 0.25, 2.54, 1.49, 2.41, 1.46, 2.68, 2.05, 1.97,
# 3.54
# )
#
# eMar <- c(
# 6.64, 6.85, 1.30, 0.00, 4.01, 2.48, 6.39, 0.00, 0.00, 1.30,
# 2.48, 1.85, 0.00, 3.00, 0.00, 3.59, 5.51, 3.00, 5.78, 4.24,
# 5.17, 2.28, 0.39, 1.85, 3.04, 3.59, 5.51, 3.10, 2.81, 4.20,
# 1.57
# )
#
# eApr <- c(
# 4.02, 3.45, 0.20, 0.18, 7.38, 2.02, 7.17, 1.10, 0.66, 0.20,
# 2.02, 5.49, 1.10, 2.75, 0.66, 3.89, 1.09, 2.75, 1.16, 0.54,
# 4.54, 0.91, 0.34, 5.49, 2.75, 3.89, 1.09, 1.63, 3.20, 1.48,
# 3.31
# )
#
# eMay <- c(
# 1.67, 7.84, 2.68, 5.76, 1.51, 1.67, 1.39, 4.06, 2.06, 2.68,
# 1.67, 4.92, 4.06, 0.00, 2.06, 2.79, 3.78, 0.00, 0.44, 1.41,
# 1.65, 3.10, 2.75, 4.92, 1.91, 2.79, 3.78, 5.78, 3.08, 4.17,
# 3.34
# )
#
# eJun <- c(
# 4.25, 4.78, 2.08, 2.77, 1.48, 9.58, 0.47, 0.00, 3.02, 2.08,
# 9.58, 9.64, 0.00, 2.29, 3.02, 2.61, 6.78, 2.29, 5.83, 2.29,
# 1.94, 4.35, 2.80, 9.64, 4.85, 2.61, 6.78, 3.04, 3.72, 2.56,
# 8.36
# )
#
# eJul <- c(
# 1.01,13.04, 3.34, 2.48, 6.79, 3.47, 0.00,10.38, 1.00, 3.34,
# 3.47, 2.25,10.38, 3.27, 1.00, 3.24, 3.29, 3.27, 7.89, 3.67,
# 4.90, 3.81, 5.54, 2.25, 3.70, 3.24, 3.29, 2.07, 1.78, 5.27,
# 3.41
# )
#
# eAug <- c(
# 4.11, 1.01, 5.56,13.27, 4.48, 1.80, 0.56, 6.64, 0.32, 5.56,
# 1.80, 2.13, 6.64, 6.28, 0.32, 3.34, 2.15, 6.28, 2.03, 5.84,
# 9.70, 9.88, 2.14, 2.13, 1.33, 3.34, 2.15, 6.62, 5.14, 2.71,
# 2.24
# )
#
# eSep <- c(
# 16.67,1.64, 0.32, 0.62, 6.68, 1.80, 0.00, 0.10, 1.84, 0.32,
# 1.80, 2.75, 0.10, 2.16, 1.84, 6.91, 3.25, 2.16, 1.41, 1.81,
# 3.48, 4.43, 1.24, 2.75, 1.57, 6.91, 3.25, 6.05, 3.85, 6.47,
# 3.45
# )
#
# eOct <- c(
# 3.46, 0.78, 2.04, 2.34, 2.20, 1.90, 0.04, 2.26, 0.12, 2.04,
# 1.90, 3.42, 2.26, 0.00, 0.12, 1.36, 1.20, 0.00, 1.24, 7.58,
# 2.97, 1.42, 3.87, 3.42, 5.68, 1.36, 1.20, 0.88, 1.99, 2.50,
# 0.79
# )
#
# eNov <- c(
# 2.26, 3.30, 3.82, 2.47, 4.12, 2.71, 0.10, 1.48, 0.12, 3.82,
# 2.71, 6.25, 1.48, 2.20, 0.12, 3.30, 4.23, 2.20, 0.91, 3.43,
# 1.49, 3.14, 6.73, 6.25, 0.53, 3.30, 4.23, 0.78, 3.14, 0.59,
# 3.15
# )
#
# eDec <- c(
# 6.19, 2.90, 0.70, 4.52, 3.45, 1.18, 0.00, 0.44, 0.00, 0.70,
# 1.18, 3.41, 0.44, 1.15, 0.00, 2.96, 5.70, 1.15, 2.04, 4.07,
# 2.84, 1.85, 7.14, 3.41, 3.06, 2.96, 5.70, 1.43, 1.40, 3.00,
# 5.24
# )