the output of a <code>mqgam</code> call.

A vector whose elements must be in (0, 1). Each element indicates a quantile of interest, 
which should be an element of <code>names(obj$fit)</code>. If left to <code>NULL</code> the function
<code>fun</code> will be applied to each of the quantile fits in <code>obj</code>.

The method or function that we want to use on the <code>gamObject</code> corresponding to quantile <code>qu</code>. For instance
<code>predict</code>, <code>plot</code> or <code>summary</code>. By default this is the identity function (<code>I</code>), which
means that the fitted model for quantile <code>qu</code> is returned.

Additional arguments to be passed to <code>fun</code>.

Contrary to <code>qgam</code>, <code>mqgam</code> does not output a standard <code>gamObject</code>, hence
 methods such as <code>predict.gam</code> or <code>plot.gam</code> cannot be used directly. <code>qdo</code>
 provides a simple wrapper for such methods.

Smooth additive quantile regression models, fitted using
the methods of Fasiolo et al. (2020) <doi:10.1080/01621459.2020.1725521>.
See Fasiolo at al. (2021) <doi:10.18637/jss.v100.i09> for an introduction to the package. Differently from
'quantreg', the smoothing parameters are estimated automatically by marginal
loss minimization, while the regression coefficients are estimated using either
PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian
credible intervals of the estimated effects have approximately the correct
coverage. The main function is qgam() which is similar to gam() in 'mgcv', but
fits non-parametric quantile regression models.

Matteo Fasiolo

qgam

Smooth Additive Quantile Regression Models

Simon N. Wood

Margaux Zaffran

Yannig Goude

Raphael Nedellec

qdo function

<dl><dt>obj</dt>
<dd>the output of a <code>mqgam</code> call.</dd>
<dt>qu</dt>
<dd>A vector whose elements must be in (0, 1). Each element indicates a quantile of interest, 
which should be an element of <code>names(obj$fit)</code>. If left to <code>NULL</code> the function
<code>fun</code> will be applied to each of the quantile fits in <code>obj</code>.</dd>
<dt>fun</dt>
<dd>The method or function that we want to use on the <code>gamObject</code> corresponding to quantile <code>qu</code>. For instance
<code>predict</code>, <code>plot</code> or <code>summary</code>. By default this is the identity function (<code>I</code>), which
means that the fitted model for quantile <code>qu</code> is returned.</dd>
<dt>...</dt>
<dd>Additional arguments to be passed to <code>fun</code>.</dd></dl>

Arguments

Matteo Fasiolo &lt;matteo.fasiolo@gmail.com&gt;.

Author

Manipulating the output of mqgam — qdo

<dl>

<dt>obj</dt>
<dd>the output of a <code>mqgam</code> call.</dd>


<dt>qu</dt>
<dd>A vector whose elements must be in (0, 1). Each element indicates a quantile of interest, 
which should be an element of <code>names(obj$fit)</code>. If left to <code>NULL</code> the function
<code>fun</code> will be applied to each of the quantile fits in <code>obj</code>.</dd>


<dt>fun</dt>
<dd>The method or function that we want to use on the <code>gamObject</code> corresponding to quantile <code>qu</code>. For instance
<code>predict</code>, <code>plot</code> or <code>summary</code>. By default this is the identity function (<code>I</code>), which
means that the fitted model for quantile <code>qu</code> is returned.</dd>


<dt>...</dt>
<dd>Additional arguments to be passed to <code>fun</code>.</dd>

</dl>

qdo: Manipulating the output of `mqgam`

Description

Usage

Value

Arguments

Author

Examples