plot.rating

Calculates ratings for two-player or
multi-player challenges. Methods included in package such as are able to
estimate ratings (players strengths) and their evolution in time, also able to
predict output of challenge. Algorithms are based on Bayesian Approximation
Method, and they don't involve any matrix inversions nor likelihood estimation.
Parameters are updated sequentially, and computation doesn't require any
additional RAM to make estimation feasible. Additionally, base of the package
is written in C++ what makes sport computation even faster. Methods used in the
package refer to Mark E. Glickman (1999)
<http://www.glicko.net/research/glicko.pdf>;
Mark E. Glickman (2001) <doi:10.1080/02664760120059219>;
Ruby C. Weng, Chih-Jen Lin (2011) <https://www.jmlr.org/papers/volume12/weng11a/weng11a.pdf>;
W. Penny, Stephen J. Roberts (1999) <doi:10.1109/IJCNN.1999.832603>.

Dawid Ka<c5><82><c4><99>dkowski

sport

Sequential Pairwise Online Rating Techniques

Dawid Kałędkowski

plot.rating function

<dl><dt>x</dt>
<dd>of class rating</dd>
<dt>n</dt>
<dd>number of teams to be plotted</dd>
<dt>players</dt>
<dd>optional vector with names of the contestants (coefficients) to plot
their evolution in time.</dd>
<dt>...</dt>
<dd>optional arguments</dd></dl>

Arguments

Plot rating object — plot.rating

<dl>

<dt>x</dt>
<dd>of class rating</dd>


<dt>n</dt>
<dd>number of teams to be plotted</dd>


<dt>players</dt>
<dd>optional vector with names of the contestants (coefficients) to plot
their evolution in time.</dd>


<dt>...</dt>
<dd>optional arguments</dd>

</dl>

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plot.rating: Plot rating object

Description

Usage

Arguments

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Description

Usage

Arguments

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