MDFS: Run end-to-end MDFS

Description Usage Arguments Details Value Examples

View source: R/main.R

Description

Run end-to-end MDFS

Usage

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MDFS(
  data,
  decision,
  n.contrast = max(ncol(data)/10, 30),
  dimensions = 1,
  divisions = NULL,
  discretizations = 1,
  range = NULL,
  pc.xi = 0.25,
  p.adjust.method = "holm",
  level = 0.05,
  seed = NULL,
  use.CUDA = FALSE
)

Arguments

data

input data where columns are variables and rows are observations (all numeric)

decision

decision variable as a boolean vector of length equal to number of observations

n.contrast

number of constrast variables (defaults to max of 1/10 of variables number and 30)

dimensions

number of dimensions (a positive integer; on CUDA limited to 2–5 range)

divisions

number of divisions (from 1 to 15; NULL selects probable optimal number)

discretizations

number of discretizations

range

discretization range (from 0.0 to 1.0; NULL selects probable optimal number)

pc.xi

parameter xi used to compute pseudocounts (the default is recommended not to be changed)

p.adjust.method

method as accepted by p.adjust ("BY" is recommended for FDR, see Details)

level

statistical significance level

seed

seed for PRNG used during discretizations (NULL for random)

use.CUDA

whether to use CUDA acceleration (must be compiled with CUDA)

Details

In case of FDR control it is recommended to use Benjamini-Hochberg-Yekutieli p-value adjustment method ("BY" in p.adjust) due to unknown dependencies between tests.

Value

A list with the following fields:

Examples

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MDFS(madelon$data, madelon$decision, dimensions = 2, divisions = 1,
     range = 0, seed = 0)

MDFS documentation built on Feb. 10, 2021, 1:08 a.m.

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