Prophet-style additive decomposition (linear trend + Fourier seasonality)
Source:R/propc.R
morie_prophet_components.RdProphet-style additive decomposition (linear trend + Fourier seasonality)
Value
Named list with \(trend, seasonal, residual, slope, intercept, fourier_terms, period, n, method\).
Examples
set.seed(1)
morie_prophet_components(x = rnorm(50))
#> $trend
#> 1 2 3 4 5 6 7
#> 0.11587831 0.11524852 0.11461872 0.11398892 0.11335912 0.11272933 0.11209953
#> 8 9 10 11 12 13 14
#> 0.11146973 0.11083994 0.11021014 0.10958034 0.10895054 0.10832075 0.10769095
#> 15 16 17 18 19 20 21
#> 0.10706115 0.10643135 0.10580156 0.10517176 0.10454196 0.10391217 0.10328237
#> 22 23 24 25 26 27 28
#> 0.10265257 0.10202277 0.10139298 0.10076318 0.10013338 0.09950358 0.09887379
#> 29 30 31 32 33 34 35
#> 0.09824399 0.09761419 0.09698439 0.09635460 0.09572480 0.09509500 0.09446521
#> 36 37 38 39 40 41 42
#> 0.09383541 0.09320561 0.09257581 0.09194602 0.09131622 0.09068642 0.09005662
#> 43 44 45 46 47 48 49
#> 0.08942683 0.08879703 0.08816723 0.08753744 0.08690764 0.08627784 0.08564804
#> 50
#> 0.08501825
#>
#> $seasonal
#> [1] -0.42111560 -0.28323859 0.08828635 0.19550630 -0.30117613 0.05806018
#> [7] 0.62349579 0.43385822 0.08210075 -0.08254563 -0.07159117 -0.32164049
#> [13] -0.42111560 -0.28323859 0.08828635 0.19550630 -0.30117613 0.05806018
#> [19] 0.62349579 0.43385822 0.08210075 -0.08254563 -0.07159117 -0.32164049
#> [25] -0.42111560 -0.28323859 0.08828635 0.19550630 -0.30117613 0.05806018
#> [31] 0.62349579 0.43385822 0.08210075 -0.08254563 -0.07159117 -0.32164049
#> [37] -0.42111560 -0.28323859 0.08828635 0.19550630 -0.30117613 0.05806018
#> [43] 0.62349579 0.43385822 0.08210075 -0.08254563 -0.07159117 -0.32164049
#> [49] -0.42111560 -0.28323859
#>
#> $residual
#> 1 2 3 4 5 6
#> -0.32121653 0.35163340 -1.03853368 1.28578558 0.51732478 -0.99125789
#> 7 8 9 10 11 12
#> -0.24816627 0.19299675 0.38284066 -0.33305290 1.47379200 0.60253318
#> 13 14 15 16 17 18
#> -0.30844573 -2.03915224 0.92958341 -0.34687126 0.17918431 0.78060427
#> 19 20 21 22 23 24
#> 0.09318344 0.05613093 0.73359425 0.76202936 0.04413338 -1.76910419
#> 25 26 27 28 29 30
#> 0.94017817 0.12697647 -0.34358544 -1.76513247 -0.27521791 0.26226719
#> 31 32 33 34 35 36
#> 0.63819936 -0.63300055 0.20984606 -0.06635442 -1.39993359 -0.18718949
#> 37 38 39 40 41 42
#> -0.06637997 0.13134938 0.91979300 0.47635323 0.04596611 -0.40147849
#> 43 44 45 46 47 48
#> -0.01595925 0.03400794 -0.85902368 -0.71248697 0.34926550 1.00389557
#> 49 50
#> 0.22312134 1.07932807
#>
#> $slope
#> [1] -0.0006297973
#>
#> $intercept
#> [1] 0.1158783
#>
#> $fourier_terms
#> X1 X2 X3 X4 X5 X6
#> -0.014019278 -0.312763433 0.138182198 0.022354881 -0.102574679 -0.213396991
#> X7 X8 X9 X10
#> -0.018612975 0.078835217 0.050470562 0.003854728
#>
#> $period
#> [1] 12
#>
#> $n
#> [1] 50
#>
#> $method
#> [1] "Prophet-style linear-trend + Fourier(K=5) seasonality"
#>