tramME (version 1.0.7)

edf_smooth.tramME: EDFs of smooth shift terms

Description

Returns an estimate of effective degrees of freedom associated with each smooth term.

Usage

# S3 method for tramME
edf_smooth(object, ...)

Value

A named vector with the edf values.

Arguments

object

A tramME object.

...

Optional arguments passed to the Hessian calculations.

Details

The EDFs are calculated by summing up the elements of $$diag(V_{\vartheta}I)$$ term-by-term. \(V_{\vartheta}\) is the joint covariance matrix of fixed and random parameters (the inverse of the joint precision, i.e., Hessian of the negative log-likelihood), and \(I\) is the joint precision of the unpenalized negative log-likelihood function. See Wood et al. (2016) or Wood (2017, Chapter 6) for references.

References

Wood, Simon N., Natalya Pya, and Benjamin Saefken (2016). "Smoothing Parameter and Model Selection for General Smooth Models." Journal of the American Statistical Association 111, <doi:10.1080/01621459.2016.1180986>

Wood, Simon N. (2017). Generalized Additive Models: An Introduction with R. Second edition. Chapman & Hall/CRC Texts in Statistical Science.

Examples

data("mcycle", package = "MASS")
fit <- LmME(accel ~ s(times), data = mcycle)
edf_smooth(fit)