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evaluate_smooth

Evaluate a smooth

Description

Evaluate a smooth at a grid of evenly spaced value over the range of the covariate associated with the smooth. Alternatively, a set of points at which the smooth should be evaluated can be supplied.

Usage

evaluate_smooth(object, ...)

## S3 method for class 'gam'
evaluate_smooth(
  object,
  smooth,
  n = 100,
  newdata = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  dist = 0.1,
  ...
)

## S3 method for class 'gamm'
evaluate_smooth(object, ...)

## S3 method for class 'list'
evaluate_smooth(object, ...)

evaluate_parametric_term(object, ...)

## S3 method for class 'gam'
evaluate_parametric_term(object, term, unconditional = FALSE, ...)

Arguments

`object`	an object of class `"gam"` or `"gamm"`.
`...`	arguments passed to other methods.
`smooth`	character; a single smooth to evaluate.
`n`	numeric; the number of points over the range of the covariate at which to evaluate the smooth.
`newdata`	a vector or data frame of points at which to evaluate the smooth.
`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.
`term`	character; which parametric term whose effects are evaulated

Value

A data frame, which is of class "evaluated_1d_smooth" or evaluated_2d_smooth, which inherit from classes "evaluated_smooth" and "data.frame".

Examples

load_mgcv()

dat <- gamSim(1, n = 400, dist = "normal", scale = 2)
m1 <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML")

evaluate_smooth(m1, "s(x1)")

## 2d example

dat <- gamSim(2, n = 1000, dist = "normal", scale = 1)
m2 <- gam(y ~ s(x, z, k = 30), data = dat$data, method = "REML")

evaluate_smooth(m2, "s(x,z)", n = 100)

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