gen_simdata

internal

Discretize multivariate continuous data using a grid
to capture the joint distribution that preserves clusters in
original data. It can handle both labeled or unlabeled data.
Both published methods (Wang et al 2020) <doi:10.1145/3388440.3412415>
and new methods are included. Joint grid discretization
can prepare data for model-free inference of association,
function, or causality.

Joe Song

GridOnClusters

Multivariate Joint Grid Discretization

Jiandong Wang

Sajal Kumar

gen_simdata function

<dl><dt>cord</dt>
<dd>data matrix that records the index for
each cluster on each dimension</dd>
<dt>sim_table</dt>
<dd>a matrix</dd>
<dt>noise</dt>
<dd>a numeric value to specify noise level</dd>
<dt>plot</dt>
<dd>a logical to turn on or off plotting</dd></dl>

Arguments

Generate Simulated Data — gen_simdata

<dl>

<dt>cord</dt>
<dd>data matrix that records the index for
each cluster on each dimension</dd>


<dt>sim_table</dt>
<dd>a matrix</dd>


<dt>noise</dt>
<dd>a numeric value to specify noise level</dd>


<dt>plot</dt>
<dd>a logical to turn on or off plotting</dd>

</dl>

gen_simdata: Generate Simulated Data

Description

Usage

Arguments