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eval_smooth

S3 methods to evaluate individual smooths

Description

S3 methods to evaluate individual smooths

Usage

eval_smooth(smooth, ...)

## S3 method for class 'mgcv.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  ...
)

## S3 method for class 'fs.interaction'
eval_smooth(
  smooth,
  model,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  ...
)

## S3 method for class 'random.effect'
eval_smooth(
  smooth,
  model,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  ...
)

## S3 method for class 'mrf.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  ...
)

## S3 method for class 't2.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  dist = 0.1,
  ...
)

## S3 method for class 'tensor.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  ...
)

Arguments

smooth

currently an object that inherits from class mgcv.smooth.
...

arguments assed to other methods
model

a fitted model; currently only mgcv::gam() and mgcv::bam() models are suported.
n

numeric; the number of points over the range of the covariate at which to evaluate the smooth.
data

an optional data frame of values to evaluate smooth at.
unconditional

logical; should confidence intervals include the uncertainty due to smoothness selection? If TRUE, the corrected Bayesian covariance matrix will be used.
overall_uncertainty

logical; should the uncertainty in the model constant term be included in the standard error of the evaluate values of the smooth?
dist

numeric; if greater than 0, this is used to determine when a location is too far from data to be plotted when plotting 2-D smooths. The data are scaled into the unit square before deciding what to exclude, and dist is a distance within the unit square. See mgcv::exclude.too.far() for further details.
gratia

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

v0.6.0
MIT + file LICENSE
Authors
Gavin L. Simpson [aut, cre] (<https://orcid.org/0000-0002-9084-8413>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>)
Initial release
2021-04-17

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