„METODY PROGNOZOWANIA GOSPODARCZEGO Z PAKIETEM R” – dataset:

9.1 Metody szacowania parametrów – dane
W <- c(2051.74, 2152.99, 2225.41, 2276.84, 2405.46, 2528.62, 2662.51, 2899.83, 3096.55, 3243.6, 3438.21, 3586.75, 3690.3, 3823.32, 3942.67, 4066.95, 4218.92, 4255.59)

M <- c(1923.98, 2062.69, 2134.68, 2201.64, 2309.52, 2402.46, 2521.16, 2739.18, 3000.11, 3156.14, 3273.88, 3458.80, 3585.86, 3706.90, 3839.77, 3968.01, 4118.63, 4271.36)

9.2 Modele adaptacyjne – dane
DaneHolt <- c(4.6956, 5.1372, 5.5152, 5.8644, 6.3924, 7.248, 9.2268, 13.9572, 17.37, 20.2056, 24.006, 28.914, 35.0208, 63.708, 248.1096, 1235.5644, 2124, 3522, 4794, 6393.6, 8431.44, 10476, 12743.16, 14873.88, 20480.88, 23085.72, 24742.2)

DaneWinters <- c(9.4, 9.3, 10.3, 10.8, 13, 14.5, 14.5, 14.2, 14, 13.4, 12, 12.3, 12.9, 12.8, 13.7, 14, 15.9, 17.9, 17.7, 17.6, 16.9, 16, 15.1, 15.1, 15.7, 15.5, 16.7, 17, 19.3, 20.6, 21, 20.4, 19.5, 18.9, 17.3, 17.2, 17.8, 17.4, 18.6, 19, 21.2, 23, 23.2, 22.5, 21.4, 20.5, 19.2, 18.7, 18.8, 18.3, 19.6, 20.1, 22, 23.7, 24.4, 24, 23.2, 22.6, 20.4, 20.4, 20.5, 20.3, 20.9, 21.3, 23.5, 25.5, 25.1, 24.3, 23.5, 22.4, 20.3, 19.8)

9.3 Modele autoregresyjne – dane
DataWIG20 <- c(14-03-31, 14-06-30, 14-09-30, 14-12-31, 15-03-31, 15-06-30, 15-09-30, 15-12-31, 16-03-31, 16-06-30, 16-09-30, 16-12-30, 17-03-31, 17-06-30, 17-09-29, 17-12-29, 18-03-30, 18-06-29)

ZamkniecieWIG20 <- c(2275.5, 1997.7, 1688.4, 1816.19, 1375.89, 1271.22, 1022.62, 1208.34, 1339.05, 1216.35, 1044.89, 1175.64, 1093.5, 1252.03, 1477.25, 1574.04, 1762.37, 1726.83, 1807.15, 1960.57, 1998.33, 2047.3, 2518.73, 2654.95, 2864.83, 2889.67, 2918.83, 3285.49, 3520.24, 3759.28, 3633.64, 3456.05, 2981.07, 2591.09, 2384.22, 1789.73, 1511.85, 1862.36, 2192.37, 2388.72, 2495.6, 2271.03, 2615.22, 2744.17, 2816.96, 2802.01, 2188.73, 2144.48, 2286.53, 2275.3, 2371.42, 2582.98, 2370.07, 2245.64, 2391.53, 2400.98, 2462.47, 2408.81, 2500.29, 2315.94, 2395.94, 2317.84, 2066.37, 1859.15, 1997.69, 1750.69, 1709.51, 1947.92, 2175.96, 2299.8, 2453.46, 2461.21, 2210.38, 2135.47)

9.4 Model VAR – dane
Średnie kwartalne wynagrodzenie nominalne brutto w gospodarce narodowej z lat 2000-2017

wynagrodzenia <- c(1868.65, 1869.78, 1905.76, 2051.74, 2043.55, 2006.92, 2047.29, 2152.99, 2155.54, 2061.95, 2095.81, 2225.41, 2228.68, 2141.01, 2160.02, 2276.84, 2332.17, 2230.53, 2269.93, 2405.46, 2415.45, 2318.53, 2347.24, 2528.62, 2530.18, 2427.27, 2464.66, 2662.51, 2709.14, 2644.34, 2703.41, 2899.83, 2983.98, 2951.36, 2968.55, 3096.55, 3185.61, 3081.48, 3113.86, 3243.6, 3316.38, 3137.85, 3203.08, 3438.21, 3466.33, 3366.11, 3416, 3586.75, 3646.09, 3496.82, 3510.22, 3690.3, 3740.05, 3612.51, 3651.72, 3823.32, 3895.31, 3739.97, 3781.14, 3942.67, 4054.89, 3854.88, 3895.33, 4066.95, 4181.49, 4019.08, 4055.04, 4218.92, 4353.55, 4220.69, 4255.59, 4255.59)

m2gus <- c(2245, 2280, 2300, 2300, 2350, 2490, 2700, 2500, 2400, 2400, 2484, 2330, 2071, 2332, 2117, 2432, 2412, 2562, 2386, 2195, 2505, 2336, 2528, 2388, 2560, 2445, 2557, 2619, 2683, 2650, 3041, 2890, 2970, 3186, 3478, 3631, 3895, 3924, 3783, 3964, 4372, 4433, 4657, 3979, 3797, 3819, 3988, 3829, 4130, 4103, 3915, 3837, 4019, 3879, 3975, 4228, 4129, 4141, 3880, 3984, 3926, 4066, 3961, 3925, 4177, 4063, 3976, 4000, 4424, 4014, 4097, 4145)

9.5 Model (G)ARCH – dane
Dane miesięczne kursu CHF/PLN z ostatniego dnia roboczego miesiąca w okresie od 31 I 1984 do 3 VIII 2018

chfpln <- rbind(0.0044, 0.0044, 0.0051, 0.005, 0.0049, 0.0049, 0.0046, 0.0047, 0.005, 0.005, 0.0051, 0.0049, 0.0052, 0.005, 0.0052, 0.0054, 0.0053, 0.0062, 0.0066, 0.0067, 0.0068, 0.0069, 0.007, 0.007, 0.0071, 0.0087, 0.0088, 0.0089, 0.0089, 0.009, 0.0095, 0.0096, 0.0121, 0.0121, 0.0119, 0.0121, 0.0125, 0.0157, 0.0158, 0.0168, 0.0174, 0.0172, 0.0174, 0.0187, 0.0196, 0.0202, 0.0232, 0.0239, 0.0233, 0.0275, 0.0287, 0.0288, 0.0297, 0.0301, 0.0291, 0.0288, 0.0304, 0.032, 0.0342, 0.0336, 0.0329, 0.0355, 0.0354, 0.0416, 0.0473, 0.0495, 0.051, 0.0625, 0.1092, 0.1481, 0.235, 0.4181, 0.6199, 0.6399, 0.63, 0.6369, 0.6692, 0.6653, 0.6899, 0.735, 0.7402, 0.7407, 0.762, 0.7477, 0.751, 0.7234, 0.6501, 0.6375, 0.7678, 0.7398, 0.7418, 0.7434, 0.756, 0.7618, 0.7822, 0.8098, 0.8037, 0.8885, 0.8994, 0.9034, 0.9339, 0.9881, 1.0273, 1.068, 1.1175, 1.0833, 1.0685, 1.0783, 1.0655, 1.0764, 1.115, 1.1529, 1.1896, 1.177, 1.1959, 1.3345, 1.383, 1.3839, 1.3978, 1.435, 1.4828, 1.5412, 1.5686, 1.5898, 1.6075, 1.6861, 1.6923, 1.741, 1.8043, 1.8394, 1.8137, 1.8612, 1.8885, 1.9561, 2.0786, 2.0662, 2.0002, 2.0326, 2.0582, 2.05, 2.1031, 2.16, 2.1447, 2.1368, 2.1026, 2.1336, 2.1735, 2.1414, 2.1381, 2.1744, 2.2591, 2.2804, 2.2347, 2.2283, 2.1879, 2.1417, 2.1106, 2.0741, 2.1199, 2.1475, 2.2604, 2.2482, 2.2873, 2.3339, 2.3489, 2.4843, 2.4747, 2.4077, 2.3906, 2.3721, 2.2627, 2.2622, 2.3524, 2.3011, 2.3023, 2.5598, 2.5862, 2.5247, 2.4991, 2.5519, 2.5896, 2.7197, 2.7022, 2.5898, 2.5963, 2.5145, 2.5802, 2.6244, 2.7269, 2.7652, 2.6644, 2.5972, 2.5506, 2.5009, 2.4845, 2.5899, 2.6106, 2.6669, 2.6036, 2.5057, 2.6229, 2.5827, 2.5785, 2.5307, 2.4696, 2.4113, 2.3485, 2.2842, 2.2187, 2.235, 2.4643, 2.5486, 2.6056, 2.5014, 2.4752, 2.3849, 2.4248, 2.4895, 2.4466, 2.4666, 2.5584, 2.7363, 2.8081, 2.756, 2.808, 2.727, 2.7056, 2.7707, 2.802, 2.8915, 3.0289, 2.8102, 2.8562, 2.8818, 2.8113, 2.8348, 2.9948, 3.0138, 3.0184, 3.0378, 3.0633, 3.0977, 3.0513, 3.0955, 3.0415, 2.9497, 2.8432, 2.8856, 2.8149, 2.8253, 2.7674, 2.6389, 2.6179, 2.5349, 2.6329, 2.783, 2.7013, 2.6069, 2.6023, 2.5987, 2.5182, 2.5637, 2.5202, 2.4673, 2.457, 2.4176, 2.4806, 2.4723, 2.5221, 2.6041, 2.5093, 2.498, 2.5025, 2.4388, 2.4036, 2.3801, 2.4146, 2.432, 2.3797, 2.3007, 2.3156, 2.274, 2.3, 2.3247, 2.2707, 2.1651, 2.1807, 2.1673, 2.2428, 2.2163, 2.2443, 2.1288, 2.077, 2.0863, 1.9654, 2.0613, 2.1517, 2.3747, 2.4492, 2.7504, 2.9888, 3.1414, 3.0751, 2.9282, 2.9878, 2.923, 2.72, 2.6967, 2.7694, 2.818, 2.7622, 2.7648, 2.7408, 2.6982, 2.7107, 2.7376, 2.8646, 3.1273, 2.9482, 3.0947, 2.9707, 2.8946, 3.08, 3.1655, 3.0483, 3.0869, 3.0999, 3.0632, 3.2219, 3.2576, 3.5316, 3.5628, 3.6322, 3.5925, 3.6713, 3.671, 3.5144, 3.4184, 3.4394, 3.4738, 3.6543, 3.5159, 3.4268, 3.4705, 3.4028, 3.4251, 3.4043, 3.3827, 3.398, 3.3954, 3.4326, 3.3954, 3.4343, 3.5181, 3.4498, 3.4704, 3.4469, 3.3908, 3.4121, 3.3836, 3.4736, 3.4232, 3.4163, 3.4405, 3.3864, 3.4207, 3.4305, 3.4868, 3.4616, 3.5061, 3.4792, 3.5621, 4.0356, 3.8863, 3.9021, 3.8615, 3.982, 4.0236, 3.9053, 3.9032, 3.9018, 3.9108, 3.9259, 3.91791, 3.98317, 4.00569, 3.87654, 3.98187, 3.96552, 4.03356, 4.02016, 3.97539, 3.93621, 3.96749, 4.13489, 4.11005, 4.04472, 4.04715, 3.9591, 3.89854, 3.84356, 3.86382, 3.71787, 3.71879, 3.76866, 3.64888, 3.59058, 3.5723, 3.59071, 3.62587, 3.58541, 3.54179, 3.74533, 3.78336, 3.69528, 3.70545)

9.6 Łańcuchy Markowa – dane
Przejścia w 4-klasowym SBM w trakcie 5 okresów

okres 1 klasa1 klasa2 klasa3 klasa4
klasa1 2 4 0 0
klasa2 3 0 7 0
klasa3 2 5 0 11
klasa4 1 2 4 9

okres 2 klasa1 klasa2 klasa3 klasa4
klasa1 3 5 0 0
klasa2 5 0 6 0
klasa3 1 2 0 8
klasa4 1 2 5 12

okres 3 klasa1 klasa2 klasa3 klasa4
klasa1 3 7 0 0
klasa2 3 0 6 0
klasa3 1 2 0 8
klasa4 0 3 5 12

okres 4 klasa1 klasa2 klasa3 klasa4
klasa1 2 5 0 0
klasa2 3 0 9 0
klasa3 2 1 0 8
klasa4 2 4 5 9

okres 5 klasa1 klasa2 klasa3 klasa4
klasa1 3 6 0 0
klasa2 2 0 8 0
klasa3 1 2 0 11
klasa4 1 3 4 9