plot.mbiglasso

Produce a plot of the coefficient paths for a fitted multiple responses
<code>mbiglasso</code> object.

models

regression

Extend lasso and elastic-net model fitting for ultra
high-dimensional, multi-gigabyte data sets that cannot be loaded into
memory. Designed to be more memory- and computation-efficient than existing
lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing
the user to analyze big data analysis even on an ordinary laptop.

Patrick Breheny

biglasso

Extending Lasso Model Fitting to Big Data

Yaohui Zeng

Chuyi Wang

plot.mbiglasso function

<dl><dt>x</dt>
<dd>Fitted <code>"mbiglasso"</code> model.</dd>
<dt>alpha</dt>
<dd>Controls alpha-blending, helpful when the number of covariates
is large. Default is alpha=1.</dd>
<dt>log.l</dt>
<dd>Should horizontal axis be on the log scale? Default is TRUE.</dd>
<dt>norm.beta</dt>
<dd>Should the vertical axis be the l2 norm of coefficients for each variable?
Default is TRUE. If False, the vertical axis is the coefficients.</dd>
<dt>...</dt>
<dd>Other graphical parameters to <code>plot</code></dd></dl>

Arguments

Chuyi Wang
Maintainer: Chuyi Wang &lt;wwaa0208@gmail.com&gt;

Author

Plot coefficients from a "mbiglasso" object — plot.mbiglasso

<dl>

<dt>x</dt>
<dd>Fitted <code>"mbiglasso"</code> model.</dd>


<dt>alpha</dt>
<dd>Controls alpha-blending, helpful when the number of covariates
is large. Default is alpha=1.</dd>


<dt>log.l</dt>
<dd>Should horizontal axis be on the log scale? Default is TRUE.</dd>


<dt>norm.beta</dt>
<dd>Should the vertical axis be the l2 norm of coefficients for each variable?
Default is TRUE. If False, the vertical axis is the coefficients.</dd>


<dt>...</dt>
<dd>Other graphical parameters to <code>plot</code></dd>

</dl>

plot.mbiglasso: Plot coefficients from a "mbiglasso" object

Description

Usage

Arguments

Author

See Also

Examples