• split_by_factor splits according to given factor

• split_within_factor splits according to given data point indices within the same level of a factor

• split_within_factor_random selects k points from each level of a factor uniformly at random as test data

• split_random splits uniformly at random

• split_data splits according to given data rows

split_by_factor(data, test, var_name = "id")

split_within_factor(data, idx_test, var_name = "id")

split_within_factor_random(data, k_test = 1, var_name = "id")

split_random(data, p_test = 0.2, n_test = NULL)

split_data(data, i_test, sort_ids = TRUE)

## Arguments

data a data frame the levels of the factor that will be used as test data name of a factor in the data indices point indices with the factor desired number of test data points per each level of the factor desired proportion of test data desired number of test data points (if NULL, p_test is used to compute this) test data row indices should the test indices be sorted into increasing order

## Value

a named list with names train, test, i_train and i_test

Other data frame handling functions: add_dis_age(), add_factor_crossing(), add_factor(), adjusted_c_hat(), new_x()