gcvplot

The <code>gcvplot</code> function loops through calls to the <code>gcv</code>
function (and hence to <code>link{locfit}</code>), using a different
smoothing parameter for each call.
The returned structure contains the GCV statistic for each fit, and can
be used to produce an GCV plot.

htest

Local regression, likelihood and density estimation methods as described in the 1999 book by Loader.

Andy Liaw

locfit

Local Regression, Likelihood and Density Estimation

Catherine Loader

Jiayang Sun

Lucent Technologies 

gcvplot function

<dl> <dt>...</dt>
<dd>arguments to the <code>gcv</code>, <code>locfit</code>
 functions.</dd> <dt>alpha</dt>
<dd>Matrix of smoothing parameters. The <code>gcvplot</code> function
 loops through calls to <code>gcv</code>, using each row of
 <code>alpha</code> as the smoothing parameter in turn. If <code>alpha</code>
 is provided as a vector, it will be converted to a one-column
 matrix, thus interpreting each component as a nearest neighbor
 smoothing parameter.</dd> <dt>df</dt>
<dd>Degrees of freedom to use as the x-axis. 2=trace(L), 
 3=trace(L'L).</dd></dl>

Arguments

Compute a generalized cross-validation plot. — gcvplot

<dl>

 <dt>...</dt>
<dd>arguments to the <code>gcv</code>, <code>locfit</code>
 functions.</dd>

 <dt>alpha</dt>
<dd>Matrix of smoothing parameters. The <code>gcvplot</code> function
 loops through calls to <code>gcv</code>, using each row of
 <code>alpha</code> as the smoothing parameter in turn. If <code>alpha</code>
 is provided as a vector, it will be converted to a one-column
 matrix, thus interpreting each component as a nearest neighbor
 smoothing parameter.</dd>

 <dt>df</dt>
<dd>Degrees of freedom to use as the x-axis. 2=trace(L), 
 3=trace(L'L).</dd>

</dl>

gcvplot: Compute a generalized cross-validation plot.

Description

Usage

Value

Arguments

See Also

Examples