S3 methods to evaluate individual smooths

S3 methods to evaluate individual smooths

Usage

eval_smooth(smooth, ...)

# S3 method for class 'mgcv.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  n_3d = NULL,
  n_4d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  dist = NULL,
  envir = NULL,
  ...
)

# S3 method for class 'soap.film'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  n_3d = NULL,
  n_4d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  clip = TRUE,
  envir = NULL,
  ...
)

# S3 method for class 'scam_smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  n_3d = NULL,
  n_4d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  dist = NULL,
  envir = NULL,
  ...
)

# S3 method for class 'fs.interaction'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  envir = NULL,
  ...
)

# S3 method for class 'sz.interaction'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  envir = NULL,
  ...
)

# S3 method for class 'random.effect'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  envir = NULL,
  ...
)

# S3 method for class 'mrf.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  envir = NULL,
  ...
)

# S3 method for class 't2.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  n_3d = NULL,
  n_4d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  dist = NULL,
  envir = NULL,
  ...
)

# S3 method for class 'tensor.smooth'
eval_smooth(
  smooth,
  model,
  n = 100,
  n_2d = NULL,
  n_3d = NULL,
  n_4d = NULL,
  data = NULL,
  unconditional = FALSE,
  frequentist = FALSE,
  overall_uncertainty = TRUE,
  dist = NULL,
  envir = NULL,
  ...
)

Arguments

smooth

currently an object that inherits from class mgcv.smooth.

...

arguments passed to other methods

model

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

n

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

n_2d

numeric; the number of points along each of the first two axes of a smooth surface, including surface panels of higher-dimensional smooths. The default is 50 in plotting and plot-preparation functions. If NULL, use n instead. Ignored when evaluation data are supplied. Factor levels are retained, and curves with only one continuous covariate use n.

n_3d, n_4d

numeric; the number of points along the third axis of a 3D smooth (n_3d, default 16), or each axis after the first two for smooths of dimension four or higher (n_4d, default 4). If NULL, use n for those axes. The first two surface axes use n_2d.

data

an optional data frame of values to evaluate smooth at.

unconditional

logical; if TRUE (and only if frequentist == FALSE) then the bayesian smoothing parameter uncertainty-corrected covariance matrix is returned, if available. Whether it is available depends on which smoothness selection method was used to fit the model.

frequentist

logical; if FALSE, the default, the bayesian covariance matrix is returned, otherwise the frequentist covariance matrix.

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.

envir

an optional environment supplying functions and constants used in model expressions. The available model formula environment is used when NULL. Covariate observations should be supplied in data.

clip

logical; should evaluation points be clipped to the boundary of a soap film smooth? The default is FALSE, which will return NA for any point that is deemed to lie outside the boundary of the soap film.