plot.swlasso

Plot the whole lasso path run by BTdecayLasso() with given lambda and path = TRUE

We utilize the Bradley-Terry Model to estimate the abilities of teams using paired comparison data. For dynamic approximation of current rankings, we employ the Exponential Decayed Log-likelihood function, and we also apply the Lasso penalty for variance reduction and grouping. The main algorithm applies the Augmented Lagrangian Method described by Masarotto and Varin (2012) <doi:10.1214/12-AOAS581>.

Yunpeng Zhou

BTdecayLasso

Bradley-Terry Model with Exponential Time Decayed Log-Likelihood
and Adaptive Lasso

Jinfeng Xu

plot.swlasso function

<dl><dt>x</dt>
<dd>Object with class "swlasso"</dd>
<dt>...</dt>
<dd>Further arguments pass to or from other methods</dd></dl>

Arguments

Plot the Lasso path — plot.swlasso

<dl>

<dt>x</dt>
<dd>Object with class "swlasso"</dd>


<dt>...</dt>
<dd>Further arguments pass to or from other methods</dd>

</dl>

plot.swlasso: Plot the Lasso path

Description

Usage

Arguments