gen_smooth

Generate simulated data for smoothing models

Provides methods to perform and analyse I-prior regression models.
Estimation is done either via direct optimisation of the log-likelihood or
an EM algorithm.

Haziq Jamil

iprior

Regression Modelling using I-Priors

gen_smooth function

<dl><dt>n</dt>
<dd>Sample size.</dd>
<dt>xlim</dt>
<dd>Limits of the <code>X</code> variables to generate from.</dd>
<dt>x.jitter</dt>
<dd>A small amount of jitter is added to the <code>X</code> variables
generated from a normal distribution with mean zero and standard deviation
equal to <code>x.jitter</code>.</dd>
<dt>seed</dt>
<dd>(Optional) Random seed.</dd></dl>

Arguments

Generate simulated data for smoothing models — gen_smooth

<dl>

<dt>n</dt>
<dd>Sample size.</dd>


<dt>xlim</dt>
<dd>Limits of the <code>X</code> variables to generate from.</dd>


<dt>x.jitter</dt>
<dd>A small amount of jitter is added to the <code>X</code> variables
generated from a normal distribution with mean zero and standard deviation
equal to <code>x.jitter</code>.</dd>


<dt>seed</dt>
<dd>(Optional) Random seed.</dd>

</dl>

gen_smooth: Generate simulated data for smoothing models

Description

Usage

Value

Arguments

Examples