The goal of kfold is to …
You can install the development version of kfold like so:
remotes::install_github("rpkgs/kfold")This is a basic example which shows you how to solve a common problem:
library(kfold)
# set.seed(1)
n <- 100 ; p <- 2
X <- matrix(rnorm(n * p), n, p) # no intercept!
y <- rnorm(n)
# r_rf <- kfold_rf(X, y)
r_lm <- kfold_lm(X, y)
#> | | | 0% | |============== | 20% | |============================ | 40% | |========================================== | 60% | |======================================================== | 80% | |======================================================================| 100%
r_lm
#> # A tibble: 6 x 11
#> R2 NSE KGE RMSE MAE Bias Bias_perc n_sim R pvalue kfold
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 0.079 -0.275 -5.06 0.869 0.588 0.455 -5.96 20 0.282 0.229 Fold1
#> 2 0.049 -0.77 -0.572 1.03 0.866 -0.533 -0.76 20 -0.222 0.348 Fold2
#> 3 0.006 -0.016 -0.657 0.957 0.747 0.121 1.08 20 0.077 0.748 Fold3
#> 4 0.005 -0.011 -0.339 1.04 0.811 -0.129 -0.342 20 0.071 0.767 Fold4
#> 5 0.054 0.035 -0.238 0.897 0.664 0.096 0.46 20 0.233 0.322 Fold5
#> 6 0.003 -0.063 -0.319 0.962 0.735 0.002 0.008 100 -0.052 0.606 all
#>
#> Folds:
#> List of 5
#> $ Fold1: int [1:20] 1 15 16 20 25 28 29 40 47 49 ...
#> $ Fold2: int [1:20] 6 7 10 14 18 32 35 37 38 44 ...
#> $ Fold3: int [1:20] 11 17 19 21 23 27 36 39 41 45 ...
#> $ Fold4: int [1:20] 9 12 13 22 24 30 31 33 34 48 ...
#> $ Fold5: int [1:20] 2 3 4 5 8 26 42 43 46 50 ...
#> NULL