Package 'fairsubset'

fairsubset

Description

Allows user to obtain subsets of columns of data or vectors within a list. These subsets will match the original data in terms of average and variation, but have a consistent length of data per column. It is intended for use on automated data generation which may not always output the same N per replicate or sample.

Usage

fairSubset(
  input_list,
  subset_setting = "mean",
  manual_N = NULL,
  random_subsets = 1000
)

Arguments

input_list	A list, data frame, or matrix. If matrix or data frame, columns should represent each sample's data.
subset_setting	Choose from c("mean", "median", "ks"). Mean or median will use these averages to choose the best subset. "ks" will use the Kolmogorov Smirnov test to choose the best subset. Defaults to "mean".
manual_N	To manually choose how many data points should be in each sample, enter an integer value here. Otherwise, fairSubset chooses the length of the sample with the most data. Defaults to NULL.
random_subsets	To manually choose how many random subsets should be used to choose the best subset, enter an integer value here. Defaults to 1000.

Value

Returns a list.

$best_subset is a data.frame containing data best representative of original data, given the parameters chosen for fairsubset

$worst_subset is a data.frame containing data as far from the original as observed in all randomly chosen subsets. It is used solely as a comparator for the worst case scenario from randomly choosing subsets

$report is a data.frame of averages and variation regarding original data, best subset, and worst subset

$warning is a character string. If != "", it represents known errors

Author(s)

Joe Delaney

Examples

input_list <- list(a= stats::rnorm(100, mean = 3, sd = 2),
b = stats::rnorm(50, mean = 5, sd = 5),
c= stats::rnorm(75, mean = 2, sd = 0.5))
fairSubset(input_list, subset_setting = "mean", manual_N = 10, random_subsets = 1000)$report

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