isDiscrete

Assumes x is numeric, length(x) &gt;= 4, and all values are finite and non-missing.

Computes the t* statistic corresponding to the tau* population
coefficient introduced by Bergsma and Dassios (2014) <DOI:10.3150/13-BEJ514>
and does so in O(n^2) time following the algorithm of Heller and
Heller (2016) <DOI:10.48550/arXiv.1605.08732> building off of the work of Weihs,
Drton, and Leung (2016) <DOI:10.1007/s00180-015-0639-x>. Also allows for
independence testing using the asymptotic distribution of t* as described by
Nandy, Weihs, and Drton (2016) <DOI:10.1214/16-EJS1166>.

Julian Karch

TauStar

Efficient Computation and Testing of the Bergsma-Dassios Sign
Covariance

Luca Weihs

Emin Martinian

isDiscrete function

<dl><dt>x</dt>
<dd>Numeric vector.</dd>
<dt>tol</dt>
<dd>Relative tolerance for "integer-like" checks.</dd>
<dt>unique_ratio</dt>
<dd>Max ratio of unique values to n to still consider discrete (must be &lt; 1).</dd>
<dt>max_levels</dt>
<dd>Max absolute number of unique values to still consider discrete.</dd></dl>

Arguments

Heuristic check for discrete numeric data — isDiscrete

<dl>

<dt>x</dt>
<dd>Numeric vector.</dd>


<dt>tol</dt>
<dd>Relative tolerance for "integer-like" checks.</dd>


<dt>unique_ratio</dt>
<dd>Max ratio of unique values to n to still consider discrete (must be &lt; 1).</dd>


<dt>max_levels</dt>
<dd>Max absolute number of unique values to still consider discrete.</dd>

</dl>

isDiscrete: Heuristic check for discrete numeric data

Description

Usage

Value

Arguments

Details