Looks how are NA distributed in each subset

evaluate_na(i, pheno)

Arguments

i

list of numeric indices of the data.frame

pheno

Data.frame

Value

The optimum value to reduce

See also

Other functions to evaluate samples: evaluate_entropy(), evaluate_independence(), evaluate_index(), evaluate_mad(), evaluate_mean(), evaluate_orig(), evaluate_sd()

Other functions to evaluate categories: evaluate_entropy(), evaluate_independence()

Other functions to evaluate numbers: evaluate_mad(), evaluate_mean(), evaluate_sd()

Examples

samples <- 10 m <- matrix(rnorm(samples), nrow = samples) m[sample(seq_len(samples), size = 5), ] <- NA # Some NA i <- create_subset(samples, 3, 4) # random subsets evaluate_na(i, m)
#> [1] 0.375