spline_values

Evaluate a spline at provided covariate values

Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.

Gavin Simpson

gratia

Graceful 'ggplot'-Based Graphics and Other Functions for GAMs
Fitted Using 'mgcv'

Gavin L. Simpson

Henrik Singmann

spline_values function

<dl><dt>smooth</dt>
<dd>currently an object that inherits from class <code>mgcv.smooth</code>.</dd>
<dt>data</dt>
<dd>a data frame of values to evaluate <code>smooth</code> at.</dd>
<dt>model</dt>
<dd>a fitted model; currently only <code><a href="/link/mgcv%3A%3Agam()?package=gratia&version=0.9.0" data-mini-rdoc="gratia::mgcv::gam()">mgcv::gam()</a></code> and <code><a href="/link/mgcv%3A%3Abam()?package=gratia&version=0.9.0" data-mini-rdoc="gratia::mgcv::bam()">mgcv::bam()</a></code>
models are suported.</dd>
<dt>unconditional</dt>
<dd>logical; should confidence intervals include the
uncertainty due to smoothness selection? If <code>TRUE</code>, the corrected Bayesian
covariance matrix will be used.</dd>
<dt>overall_uncertainty</dt>
<dd>logical; should the uncertainty in the model
constant term be included in the standard error of the evaluate values of
the smooth?</dd>
<dt>frequentist</dt>
<dd>logical; use the frequentist covariance matrix?</dd></dl>

Arguments

Evaluate a spline at provided covariate values — spline_values

<dl>

<dt>smooth</dt>
<dd>currently an object that inherits from class <code>mgcv.smooth</code>.</dd>


<dt>data</dt>
<dd>a data frame of values to evaluate <code>smooth</code> at.</dd>


<dt>model</dt>
<dd>a fitted model; currently only <code><a href='https://rdrr.io/pkg/mgcv/man/gam.html'>mgcv::gam()</a></code> and <code><a href='https://rdrr.io/pkg/mgcv/man/bam.html'>mgcv::bam()</a></code>
models are suported.</dd>


<dt>unconditional</dt>
<dd>logical; should confidence intervals include the
uncertainty due to smoothness selection? If <code>TRUE</code>, the corrected Bayesian
covariance matrix will be used.</dd>


<dt>overall_uncertainty</dt>
<dd>logical; should the uncertainty in the model
constant term be included in the standard error of the evaluate values of
the smooth?</dd>


<dt>frequentist</dt>
<dd>logical; use the frequentist covariance matrix?</dd>

</dl>

spline_values: Evaluate a spline at provided covariate values

Description

Usage

Arguments