Extract the covariance matrix of the model parameters or a subset of these for a particular model term

Usage

get_vcov(
  object,
  unconditional = FALSE,
  frequentist = FALSE,
  term = NULL,
  by_level = NULL
)

# S3 method for class 'scam'
get_vcov(
  object,
  unconditional = FALSE,
  frequentist = FALSE,
  term = NULL,
  by_level = NULL
)

Arguments

object: an R object from which a covariance matrix shall be extracted.
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.
term: character, length 1; return the subset of the covariance matrix for a particular smooth term. Only a single term can be selected.
by_level: character; currently unsued.

Value

a matrix containing the selected covariance matrix.

Details

For mgcv::scasm() fits with linear inequality constraints, the Gaussian covariance approximation does not enforce the fitted shapes. Pointwise intervals calculated from this matrix can extend outside those constraints. See post_draws() for sampling and native-bootstrap details.

Author

Gavin L. Simpson