Lineárna regresia
Yt <- c(6.1, 7.3, 9.6, 10.2, 10.1, 11.3, 12.2, 12.5, 13.2)
Pt <- c(103, 102, 100, 94, 98, 97, 98, 97, 96)
It <- c(110, 114, 130, 135, 141, 152, 160, 165, 170)

Autokorelácia
Yt <- c(292.5, 308.7, 333, 351.5, 371.9, 381.7, 378.5, 396.4, 417.6, 414.4, 428.4, 420.2, 436.2, 451.3, 476)
Xt <- c(6399, 7300, 8259, 9331, 10108, 10833, 11535, 12470, 13616, 14470, 15930, 15982, 17220, 17850, 19500)

Heteroskedasticita
Yt <- c(2, 3, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 20, 21)
Xt <- c(14, 20, 28, 40, 42, 50, 58, 65, 72, 73, 82, 85, 93, 112, 128, 142)
Pt <- c(11, 11, 11, 10, 6, 6, 6, 6, 6, 5, 5, 5, 5, 1, 1, 1)

Multikolinearita
Yt <- c(100, 102, 104, 105, 103, 108, 109, 112, 115, 120)
Xt1 <- c(50, 49, 56, 58, 62, 63, 65, 68, 70, 71)
Xt2 <- c(10, 12, 11, 13, 15, 16, 16, 18, 20, 22)
Xt3 <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

Simultánne modely
Ct <- c(167.5, 156.2, 167.2, 169.8, 188.8, 186.5, 195.7, 187.6, 203.6)
Yt <- c(321.8, 345.2, 334.4, 319.9, 343, 367.9, 350.3, 339.1, 360.7)
Ct1 <- c(144.1, 167.5, 156.2, 167.2, 169.8, 188.8, 186.5, 195.7, 187.6)
It <- c(3.14, 3.43, 3.41, 3.31, 3.12, 3.11, 3.02, 2.96, 2.93)
Mt <- c(770.2, 792.7, 876.4, 856.6, 888.1, 959.8, 1012.3, 1014.3, 1053.9)
rt <- c(2.05, 2.89, 2.85, 1.24, 2.8, 3.36, 2.48, 2.11, 1.17)
It1 <- c(2.81, 3.14, 3.43, 3.41, 3.31, 3.12, 3.11, 3.02, 2.96)

Exponenciálne vyrovnávanie, nesezónne dáta
yt <- c(14.29, 13.81, 13.58, 13.88, 14.26, 13.67, 12.60, 13.44, 13.39, 13.59, 13.25, 12.90, 12.71, 11.89, 11.93, 12.30, 11.61, 11.41, 11.33, 11.33, 11.33, 10.87)

Exponenciálne vyrovnávanie, sezónne dáta
yt <- c(93.2, 96.0, 95.2, 77.1, 70.9, 64.8, 70.1, 77.3, 79.5, 100.6, 100.7, 107.1, 95.9, 82.8, 83.3, 80.0, 80.4, 67.5, 75.7, 71.1, 89.3, 101.1, 105.2, 114.1, 96.3, 84.4, 91.2, 81.9, 80.5, 70.4, 74.8, 75.9, 86.3, 98.7, 100.9, 113.8, 89.8, 84.4, 87.2, 85.6, 72.0, 69.2, 77.5, 78.1, 94.3, 97.7, 100.2, 116.4, 97.1, 93.0, 96.0, 80.5, 76.1, 69.9, 73.6, 92.6, 94.2, 93.5, 108.5, 109.4, 105.1, 92.5, 97.1, 81.4, 79.1, 72.1, 78.7, 87.1, 91.4, 109.9, 116.3, 113.0, 100.0, 84.8, 94.3, 87.1, 90.3, 72.4, 84.9, 92.7, 92.2, 114.9, 112.5, 118.3, 106.0, 91.2, 96.6, 96.3, 88.2, 70.2, 86.5, 88.2, 102.8, 119.1, 119.2, 125.1, 106.1, 102.1, 105.2, 101.0, 84.3, 87.5, 92.7, 94.4, 113.0, 113.9, 122.9, 132.7, 106.9, 96.6, 127.3, 98.2, 100.2, 89.4, 95.3, 104.2, 106.4, 116.2, 135.9, 134.0, 104.6, 107.1, 123.5, 98.8, 98.6, 90.6, 89.1, 105.2, 114.0, 122.1, 138.0, 142.2, 116.4, 112.6, 123.8, 103.6, 113.9, 98.6, 95.0, 116.0, 113.9, 127.5, 131.4, 145.9, 131.5, 131.0, 130.5, 118.9, 114.3, 85.7, 104.6, 105.1, 117.3, 142.5, 140.0, 159.8, 131.2, 125.4, 126.5, 119.4, 113.5, 98.7, 114.5, 113.8, 133.1, 143.4, 137.3, 165.2, 126.9, 124.0, 135.7, 130.0, 109.4, 117.8, 120.3, 121.0, 132.3, 142.9, 147.4, 175.9, 132.6, 123.7, 153.3, 134.0, 119.6, 116.2, 118.6, 130.7, 129.3, 144.4, 163.2, 179.4, 128.1, 138.4, 152.7, 120.0, 140.5, 116.2, 121.4, 127.8, 143.6, 157.6, 166.2, 182.3, 153.1, 147.6, 157.7, 137.2, 151.5, 98.7, 145.8, 151.7, 129.4, 174.1, 197.0, 193.9, 164.1, 142.8, 157.9, 159.2, 162.2, 123.1, 130.0, 150.1, 169.4, 179.7, 182.1, 194.3, 161.4, 169.4, 168.8, 158.1, 158.5, 135.3, 149.3, 143.4, 142.2, 188.4, 166.2, 199.2, 182.7, 145.2, 182.1, 158.7, 141.6, 132.6, 139.6, 147.0, 166.6, 157.0, 180.4, 210.2, 159.8, 157.8, 168.2, 158.4, 152.0, 142.2, 137.2, 152.6, 166.8, 165.6, 198.6, 201.5, 170.7, 164.4, 179.7, 157.0, 168.0, 139.3, 138.6, 153.4, 138.9, 172.1, 198.4, 217.8, 173.7, 153.8, 175.6, 147.1, 160.3, 135.2, 148.8, 151.0, 148.2, 182.2, 189.2, 183.1, 170.0, 158.4, 176.1, 156.2, 153.2, 117.9, 149.8, 156.6, 166.7, 156.8, 158.6, 210.8, 203.6, 175.2, 168.7, 155.9, 147.3, 137.0, 141.1, 167.4, 160.2, 191.9, 174.4, 208.2, 159.4, 161.1, 172.1, 158.4, 114.6, 159.6, 159.7, 159.4, 160.7, 165.5, 205.0, 205.2, 141.6, 148.1, 184.9, 132.5, 137.3, 135.5, 121.7, 166.1, 146.8, 162.8, 186.8, 185.5, 151.5, 158.1, 143.0, 151.2, 147.6, 130.7, 137.5, 146.1, 133.6, 167.9, 181.9, 202.0, 166.5, 151.3, 146.2, 148.3, 144.7, 123.6, 151.6, 133.9, 137.4, 181.6, 182.0, 190.0, 161.2, 155.5, 141.9, 164.6, 136.2, 126.8, 152.5, 126.6, 150.1, 186.3, 147.5, 200.4, 177.2, 127.4, 177.1, 154.4, 135.2, 126.4, 147.3, 140.6, 152.3, 151.2, 172.2, 215.3, 154.1, 159.3, 160.4, 151.9, 148.4, 139.6, 148.2, 153.5, 145.1, 183.7, 210.5, 203.3, 153.3, 144.3, 169.6, 143.7, 160.1, 135.6, 141.8, 159.9, 145.7, 183.5, 198.2, 186.8, 172.0, 150.6, 163.3, 153.7, 152.9, 135.5, 148.5, 148.4, 133.6, 194.1, 208.6, 197.3, 164.4, 148.1, 152.0, 144.1, 155.0, 124.5, 153.0, 146.0, 138.0, 190.0, 192.0, 192.0, 147.0, 133.0, 163.0, 150.0, 129.0, 131.0, 145.0, 137.0, 138.0, 168.0, 176.0, 188.0, 139.0, 143.0, 150.0, 154.0, 137.0, 129.0, 128.0, 140.0, 143.0, 151.0, 177.0, 184.0, 151.0, 134.0, 164.0, 126.0, 131.0, 125.0, 127.0, 143.0, 143.0, 160.0, 190.0, 182.0, 138.0, 136.0, 152.0, 127.0, 151.0, 130.0, 119.0, 153.0)

Brownovo exponenciálne vyrovnávanie
data <- c(14.29, 13.81, 13.58, 13.88, 14.26, 13.67, 12.6, 13.44, 13.39,13.59, 13.25, 12.9, 12.71, 11.89,11.93, 12.3, 11.61, 11.41,11.33, 11.33, 11.3, 10.87)

ARIMA modely
yt <- c(29.33, 19.98, 25.76, 29, 31.03, 32.68, 33.56, 27.5, 26.75, 30.55, 28.94, 28.5, 28.19, 26.13, 27.79, 27.63, 29.89, 28.18, 26.65, 30.01, 30.8, 30.45, 36.61, 31.4, 30.83, 33.22, 30.15, 27.08, 33.66, 36.58, 29.04, 28.08, 30.28, 29.35, 33.6, 30.29, 20.11, 17.51, 23.71, 24.22, 32.43, 32.44, 29.39, 23.45, 23.62, 28.12, 29.94, 30.56, 32.3, 31.58, 27.99, 24.13, 29.2, 34.3, 26.41, 28.78, 21.28, 21.71, 21.47, 24.71, 33.61, 36.54, 35.7, 33.68, 29.29, 25.12, 27.23, 30.61, 29.06, 28.48, 32.01, 31.89, 31.72, 29.02, 31.92, 24.28, 22.69, 26.6, 28.86, 28.27, 28.17, 28.58, 30.76, 30.62, 20.84, 16.57, 25.23, 31.79, 32.52, 30.28, 26.14, 19.03, 24.34, 31.58, 31.95, 31.68, 29.1, 23.15, 26.74, 32.44)

ARCH/GARCH modely
data <- c(29.33, 19.98, 25.76, 29, 31.03, 32.68, 33.56, 27.5, 26.75, 30.55, 28.94, 28.5, 28.19, 26.13, 27.79, 27.63, 29.89, 28.18, 26.65, 30.01, 30.8, 30.45, 36.61, 31.4, 30.83, 33.22, 30.15, 27.08, 33.66, 36.58, 29.04, 28.08, 30.28, 29.35, 33.6, 30.29, 20.11, 17.51, 23.71, 24.22, 32.43, 32.44, 29.39, 23.45, 23.62, 28.12, 29.94, 30.56, 32.3, 31.58, 27.99, 24.13, 29.2, 34.3, 26.41, 28.78, 21.28, 21.71, 21.47, 24.71, 33.61, 36.54, 35.7, 33.68, 29.29, 25.12, 27.23, 30.61, 29.06, 28.48, 32.01, 31.89, 31.72, 29.02, 31.92, 24.28, 22.69, 26.6, 28.86, 28.27, 28.17, 28.58, 30.76, 30.62, 20.84, 16.57, 25.23, 31.79, 32.52, 30.28, 26.14, 19.03, 24.34, 31.58, 31.95, 31.68, 29.1, 23.15, 26.74, 32.44)

Kalmanová filtrácia
data <- c(29.33, 19.98, 25.76, 29, 31.03, 32.68, 33.56, 27.5, 26.75, 30.55, 28.94, 28.5, 28.19, 26.13, 27.79, 27.63, 29.89, 28.18, 26.65, 30.01, 30.8, 30.45, 36.61, 31.4, 30.83, 33.22, 30.15, 27.08, 33.66, 36.58, 29.04, 28.08, 30.28, 29.35, 33.6, 30.29, 20.11, 17.51, 23.71, 24.22, 32.43, 32.44, 29.39, 23.45, 23.62, 28.12, 29.94, 30.56, 32.3, 31.58, 27.99, 24.13, 29.2, 34.3, 26.41, 28.78, 21.28, 21.71, 21.47, 24.71, 33.61, 36.54, 35.7, 33.68, 29.29, 25.12, 27.23, 30.61, 29.06, 28.48, 32.01, 31.89, 31.72, 29.02, 31.92, 24.28, 22.69, 26.6, 28.86, 28.27, 28.17, 28.58, 30.76, 30.62, 20.84, 16.57, 25.23, 31.79, 32.52, 30.28, 26.14, 19.03, 24.34, 31.58, 31.95, 31.68, 29.1, 23.15, 26.74, 32.44)

data <- c(1359.484483, 2052.173809, 5915.54876, 1012.961449, 1168.220137, 1659.216271, 5682.493342, 1073.289206, 1446.10269, 1940.171824, 5576.950046, 978.3632247, 1410.891098, 1500.214099, 5068.241408, 953.8607813, 1338.309843, 2036.406511, 5005.75477, 1052.939032, 1488.870643, 1938.823023, 5130.361492, 1347.808594, 1516.837452, 1922.73126, 5792.78566, 1220.651136, 1431.4242, 1754.181177, 5648.294554, 1355.087362)