Update a locally-weighted PLS specification

Usage

# S3 method for class 'lwpls'
update(
  object,
  parameters = NULL,
  num_comp = NULL,
  localization = NULL,
  neighbors = NULL,
  similarity = NULL,
  sparsity = NULL,
  fresh = FALSE,
  ...
)

Arguments

object: A lwpls() model specification.
parameters: A 1-row tibble or named list with main parameters to update. Use either parameters or the main arguments directly when updating. If the main arguments are used, these will supersede the values in parameters. Also, using engine arguments in this object will result in an error.
num_comp: The number of PLS components (latent variables) in each local model (engine default: 2).
localization: A positive number controlling how local the models are (engine default: 1). Small values give large weights to the closest training samples only; large values give all samples similar weights, so that LW-PLS tends to a global PLS model. See Details.
neighbors: The number of nearest training samples used for each local model. The default (NULL) uses all training samples, as in the original LW-PLS algorithm.
similarity: The similarity index: "euclidean" (engine default) or "covariance" for covariance-based LW-PLS (CbLW-PLS). See Details and similarity().
sparsity: A number in [0, 1): the sparsity threshold \(\eta\) of the local models (engine default: 0, no sparsity). See Details and sparsity().
fresh: A logical for whether the arguments should be modified in-place or replaced wholesale.
...: Not used for update().

Value

An updated model specification.

Examples

spec <- lwpls(num_comp = 3)
spec
#> Locally-Weighted PLS Model Specification (unknown mode)
#> 
#> Main Arguments:
#>   num_comp = 3
#> 
#> Computational engine: lwpls 
#> 
update(spec, localization = 0.25)
#> Locally-Weighted PLS Model Specification (unknown mode)
#> 
#> Main Arguments:
#>   num_comp = 3
#>   localization = 0.25
#> 
#> Computational engine: lwpls 
#> 
update(spec, localization = 0.25, fresh = TRUE)
#> Locally-Weighted PLS Model Specification (unknown mode)
#> 
#> Main Arguments:
#>   localization = 0.25
#> 
#> Computational engine: lwpls 
#>