MICorrBoots: Mutual information with weighted bootstrap

In mrmtshmp/ExploratoryDataAnalysis: Make plots for explanatory data analyses

Description

Mutual information with weighted bootstrap

Usage

MICorrBoots(
  X,
  Y,
  S = NULL,
  method = "emp",
  disc.X = "equalfreq",
  disc.Y = "equalfreq",
  alpha = 0.6,
  n.sim = 2000,
  group = ADS$subjID,
  samp.prob = rep(1/length(unique(ADS$subjID)), length(unique(ADS$subjID))),
  ...
)

Arguments

X	<object; input> A numeric vector.
Y	<object; input> A numeric vector.
method	<character; proccessing> a method for estimation of entropy. (see help of infotheo- or minerva-package)
disc.X	<character; proccessing> a method for discretization of X.
disc.Y	<character; proccessing> a method for discretization of Y.
alpha	<numeric; proccessing> alpha parameter for the mine method. (works only when *method* is "mine")
n.sim	<numeric; proccessing> The number of simulation.
group	<vector; proccessing> Ve
samp.prob	<numeric vector; proccessing> probability
...	Parameters to be passed to the function *minerva::mine*.

Examples

eg.res.MICorrBoots <- MICorrBoots(
X = c( 1,  1,  2,  3,  5,  2,  2,  3,  1),
Y = c( 1,  1,  2,  3,  5,  1,  1,  1,  2),
S = c('A','A','A','A','A','B','B','B','B'),
method='shrink',
disc.X='none',
disc.Y='none',
alpha = NULL,
n.sim = 50,
group = c('A','A','A','A','A','B','B','B','B'),
samp.prob =
  rep(
   1/length( unique( c('A','A','A','A','A','B','B','B','B'))),
   length( unique( c('A','A','A','A','A','B','B','B','B')))
   )
  )

mrmtshmp/ExploratoryDataAnalysis documentation built on Oct. 6, 2020, 8 a.m.