gratia (version 0.10.0)

smooth_estimates: Evaluate smooths at covariate values

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. smooth_estimates() is a new implementation of evaluate_smooth(), and replaces that function, which has been removed from the package.

Usage

smooth_estimates(object, ...)
# S3 method for gam
smooth_estimates(
  object,
  select = NULL,
  smooth = deprecated(),
  n = 100,
  n_3d = 16,
  n_4d = 4,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE,
  dist = NULL,
  unnest = TRUE,
  partial_match = FALSE,
  ...
)

Value

A data frame (tibble), which is of class "smooth_estimates".

Arguments

object

an object of class "gam" or "gamm".

...

arguments passed to other methods.

select

character; select which smooth's posterior to draw from. The default (NULL) means the posteriors of all smooths in model wil be sampled from. If supplied, a character vector of requested terms.

smooth

Use select instead.

n

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

n_3d, n_4d

numeric; the number of points over the range of last covariate in a 3D or 4D smooth. The default is NULL which achieves the standard behaviour of using n points over the range of all covariate, resulting in n^d evaluation points, where d is the dimension of the smooth. For d > 2 this can result in very many evaluation points and slow performance. For smooths of d > 4, the value of n_4d will be used for all dimensions > 4, unless this is NULL, in which case the default behaviour (using n for all dimensions) will be observed.

data

a data frame of covariate values 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.

unnest

logical; unnest the smooth objects?

partial_match

logical; in the case of character select, should select match partially against smooths? If partial_match = TRUE, select must only be a single string, a character vector of length 1.

Examples

load_mgcv()
# \dontshow{
op <- options(cli.unicode = FALSE, pillar.sigfig = 6)
# }
dat <- data_sim("eg1", n = 400, dist = "normal", scale = 2, seed = 2)
m1 <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML")

## evaluate all smooths
smooth_estimates(m1)

## or selected smooths
smooth_estimates(m1, select = c("s(x0)", "s(x1)"))
# \dontshow{
options(op)
# }