Assign folds for cross-validation

If y has only two unique values, fold assignments are chosen so that the balance between outcomes is the same in each fold. This is useful for logistic regression and time-to-event data (to balance the fraction of observations that are censored).

Usage

assign_fold(y, folds, seed)

Arguments

y

Either (i) the vector of outcomes or (ii) a vector such as 1:n

folds

Number of folds

seed

(optional) set a seed for reproducibility

Value

A vector of integers indicating fold assignments

See also

[cv.ncvreg()]

Examples

assign_fold(rnorm(11), 2)
#>  [1] 2 1 1 1 1 2 1 2 2 2 1
assign_fold(1:41, 7)
#>  [1] 3 2 3 1 3 3 2 4 2 7 5 6 4 1 6 7 5 5 6 4 5 1 7 2 5 3 4 6 7 2 3 7 1 1 5 1 4 6
#> [39] 2 4 6
assign_fold(1:41, 7) |> table()
#> 
#> 1 2 3 4 5 6 7 
#> 6 6 6 6 6 6 5 
data(Heart)
assign_fold(Heart$y, 7) |> head()
#> [1] 2 5 1 4 2 3
assign_fold(Heart$y, 7) |> table(Heart$y)
#>    
#>      0  1
#>   1 43 23
#>   2 43 23
#>   3 43 23
#>   4 43 23
#>   5 43 23
#>   6 43 23
#>   7 44 22