Produce a forecast from a solarModel object

solarModel_predict(model, moments, lambda = 0, ci = 0.01)

Arguments

lambda

Numeric scalar, Sugeno parameter.

Note

Version 1.0.0.

Examples

model = solarModel$new(spec)
model$fit()
#> No outliers!
moments <- model$moments$conditional[14,]
object <- solarModel_predict(model, moments, ci = 0.01)
object
#> $grid
#> # A tibble: 100 × 4
#>        x pdf_Rt_mix pdf_Rt_mix_up pdf_Rt_mix_dw
#>    <dbl>      <dbl>         <dbl>         <dbl>
#>  1 0.216   0.000275      0.000275      1.65e-26
#>  2 0.239   0.00386       0.00386       3.99e-20
#>  3 0.262   0.0137        0.0137        8.19e-17
#>  4 0.285   0.0295        0.0295        1.19e-14
#>  5 0.308   0.0501        0.0501        4.46e-13
#>  6 0.331   0.0736        0.0736        7.34e-12
#>  7 0.354   0.0987        0.0987        7.02e-11
#>  8 0.377   0.124         0.124         4.58e-10
#>  9 0.400   0.149         0.149         2.25e- 9
#> 10 0.423   0.174         0.174         8.93e- 9
#> # ℹ 90 more rows
#> 
#> $df_n
#> # A tibble: 1 × 36
#>   date        Year Month   Day     e_Yt sd_Yt   M_Y1  S_Y1  M_Y0  S_Y0 theta
#>   <date>     <dbl> <dbl> <int>    <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2005-01-14  2005     1    14 -0.00741 0.996 -0.559 0.881 0.660 0.473     0
#> # ℹ 25 more variables: p1 <dbl>, GHI_bar <dbl>, Ct <dbl>, alpha <dbl>,
#> #   beta <dbl>, e_Rt <dbl>, e_Rt_up <dbl>, e_Rt_dw <dbl>, v_Rt <dbl>,
#> #   v_Rt_up <dbl>, v_Rt_dw <dbl>, ci_mix_lo <dbl>, ci_mix_hi <dbl>,
#> #   ci_up_lo <dbl>, ci_up_hi <dbl>, ci_dw_lo <dbl>, ci_dw_hi <dbl>,
#> #   pdf_e_Rt <dbl>, pdf_ci_mix_lo <dbl>, pdf_ci_mix_hi <dbl>,
#> #   pdf_ci_up_lo <dbl>, pdf_ci_up_hi <dbl>, pdf_ci_dw_lo <dbl>,
#> #   pdf_ci_dw_hi <dbl>, Rt <dbl>
#> 
#> $ci
#> [1] 0.01
#> 
#> attr(,"class")
#> [1] "solarModelForecast" "list"