fitNN

Helpful mini function to fit the nearest neighbor (NN) algorithm given a set and
defined distance

Trace plots and convergence diagnostics for Markov Chain Monte Carlo (MCMC) algorithms on highly multivariate or unordered spaces. Methods outlined in a forthcoming paper.

Luke Duttweiler

genMCMCDiag

Generalized Convergence Diagnostics for Difficult MCMC
Algorithms

fitNN function

<dl><dt>uniqueDraws</dt>
<dd>List of unique values that make up the set on which we are using
the NN algorithm</dd>
<dt>uniqueLabels</dt>
<dd>List of unique labels associated 1-1 with the unique values</dd>
<dt>distance</dt>
<dd>Function with arguments x,y that returns a distance
defined on the given values</dd>
<dt>minDist</dt>
<dd>Minimum possible distance between two points that aren't equivalent.
May be ignored, but if possible to specify, may speed up the algorithm.</dd></dl>

Arguments

Helpful mini function to fit the nearest neighbor (NN) algorithm given a set and
defined distance — fitNN

<dl>

<dt>uniqueDraws</dt>
<dd>List of unique values that make up the set on which we are using
the NN algorithm</dd>


<dt>uniqueLabels</dt>
<dd>List of unique labels associated 1-1 with the unique values</dd>


<dt>distance</dt>
<dd>Function with arguments x,y that returns a distance
defined on the given values</dd>


<dt>minDist</dt>
<dd>Minimum possible distance between two points that aren't equivalent.
May be ignored, but if possible to specify, may speed up the algorithm.</dd>

</dl>

fitNN: Helpful mini function to fit the nearest neighbor (NN) algorithm given a set and defined distance

Description

Usage

Value

Arguments