Specification of scenarios of a solarModel
solarScenario_filter(spec, residuals)Version 1.0.2
model <- solarModel$new(spec)
model$fit()
#> No outliers!
# Specification
spec <- solarScenario_spec$new(model)
residuals <- solarScenario_residuals(spec, 4, 1)
solarScenario_filter(spec, residuals)
#> Simulation: 1/4 (25 %)
#> Simulation: 2/4 (50 %)
#> Simulation: 3/4 (75 %)
#> Simulation: 4/4 (100 %)
#> [[1]]
#> # A tibble: 366 × 21
#> nsim date n Year Month Day GHI clearsky Xt Yt
#> <int> <date> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2009-12-31 365 2009 12 31 0.699 1.79 0.686 -1.21
#> 2 1 2010-01-01 1 2010 1 1 1.48 1.80 0.340 0.00143
#> 3 1 2010-01-02 2 2010 1 2 0.573 1.77 0.746 -1.54
#> 4 1 2010-01-03 3 2010 1 3 0.769 2.19 0.662 -1.10
#> 5 1 2010-01-04 4 2010 1 4 0.937 1.99 0.591 -0.804
#> 6 1 2010-01-05 5 2010 1 5 1.07 2.03 0.535 -0.605
#> 7 1 2010-01-06 6 2010 1 6 1.80 2.12 0.225 0.347
#> 8 1 2010-01-07 7 2010 1 7 0.735 2.12 0.687 -1.22
#> 9 1 2010-01-08 8 2010 1 8 1.39 1.96 0.415 -0.223
#> 10 1 2010-01-09 9 2010 1 9 2.13 2.05 0.108 0.768
#> # ℹ 356 more rows
#> # ℹ 11 more variables: Yt_tilde <dbl>, eps <dbl>, eps_tilde <dbl>, sigma <dbl>,
#> # u_tilde <dbl>, B <dbl>, z1 <dbl>, z2 <dbl>, GHI_bar <dbl>, theta <dbl>,
#> # z <dbl>
#>
#> [[2]]
#> # A tibble: 366 × 21
#> nsim date n Year Month Day GHI clearsky Xt Yt
#> <int> <date> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 2 2009-12-31 365 2009 12 31 0.699 1.79 0.686 -1.21
#> 2 2 2010-01-01 1 2010 1 1 0.993 1.80 0.557 -0.682
#> 3 2 2010-01-02 2 2010 1 2 0.525 1.77 0.768 -1.69
#> 4 2 2010-01-03 3 2010 1 3 1.89 2.19 0.168 0.536
#> 5 2 2010-01-04 4 2010 1 4 1.12 1.99 0.510 -0.518
#> 6 2 2010-01-05 5 2010 1 5 1.46 2.03 0.367 -0.0783
#> 7 2 2010-01-06 6 2010 1 6 1.50 2.12 0.355 -0.0439
#> 8 2 2010-01-07 7 2010 1 7 1.96 2.12 0.167 0.541
#> 9 2 2010-01-08 8 2010 1 8 2.05 1.96 0.136 0.655
#> 10 2 2010-01-09 9 2010 1 9 1.23 2.05 0.487 -0.446
#> # ℹ 356 more rows
#> # ℹ 11 more variables: Yt_tilde <dbl>, eps <dbl>, eps_tilde <dbl>, sigma <dbl>,
#> # u_tilde <dbl>, B <dbl>, z1 <dbl>, z2 <dbl>, GHI_bar <dbl>, theta <dbl>,
#> # z <dbl>
#>
#> [[3]]
#> # A tibble: 366 × 21
#> nsim date n Year Month Day GHI clearsky Xt Yt
#> <int> <date> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 3 2009-12-31 365 2009 12 31 0.699 1.79 0.686 -1.21
#> 2 3 2010-01-01 1 2010 1 1 0.639 1.80 0.715 -1.36
#> 3 3 2010-01-02 2 2010 1 2 0.631 1.77 0.720 -1.39
#> 4 3 2010-01-03 3 2010 1 3 1.28 2.19 0.435 -0.282
#> 5 3 2010-01-04 4 2010 1 4 1.52 1.99 0.335 0.0158
#> 6 3 2010-01-05 5 2010 1 5 1.28 2.03 0.444 -0.308
#> 7 3 2010-01-06 6 2010 1 6 1.07 2.12 0.538 -0.615
#> 8 3 2010-01-07 7 2010 1 7 1.50 2.12 0.361 -0.0605
#> 9 3 2010-01-08 8 2010 1 8 1.85 1.96 0.220 0.364
#> 10 3 2010-01-09 9 2010 1 9 2.29 2.05 0.0427 1.13
#> # ℹ 356 more rows
#> # ℹ 11 more variables: Yt_tilde <dbl>, eps <dbl>, eps_tilde <dbl>, sigma <dbl>,
#> # u_tilde <dbl>, B <dbl>, z1 <dbl>, z2 <dbl>, GHI_bar <dbl>, theta <dbl>,
#> # z <dbl>
#>
#> [[4]]
#> # A tibble: 366 × 21
#> nsim date n Year Month Day GHI clearsky Xt Yt
#> <int> <date> <dbl> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 4 2009-12-31 365 2009 12 31 0.699 1.79 0.686 -1.21
#> 2 4 2010-01-01 1 2010 1 1 1.16 1.80 0.485 -0.437
#> 3 4 2010-01-02 2 2010 1 2 0.656 1.77 0.709 -1.33
#> 4 4 2010-01-03 3 2010 1 3 1.60 2.19 0.298 0.126
#> 5 4 2010-01-04 4 2010 1 4 2.09 1.99 0.0852 0.873
#> 6 4 2010-01-05 5 2010 1 5 1.75 2.03 0.242 0.293
#> 7 4 2010-01-06 6 2010 1 6 1.99 2.12 0.146 0.617
#> 8 4 2010-01-07 7 2010 1 7 1.94 2.12 0.175 0.510
#> 9 4 2010-01-08 8 2010 1 8 1.40 1.96 0.408 -0.200
#> 10 4 2010-01-09 9 2010 1 9 1.99 2.05 0.168 0.537
#> # ℹ 356 more rows
#> # ℹ 11 more variables: Yt_tilde <dbl>, eps <dbl>, eps_tilde <dbl>, sigma <dbl>,
#> # u_tilde <dbl>, B <dbl>, z1 <dbl>, z2 <dbl>, GHI_bar <dbl>, theta <dbl>,
#> # z <dbl>
#>