deviance: Smooth Model Deviance

In npreg: Nonparametric Regression via Smoothing Splines

Smooth Model Deviance

Description

Returns the deviance from a fit smoothing spline (fit by ss), smooth model (fit by sm), or generalized smooth model (fit by gsm).

Usage

## S3 method for class 'gsm'
deviance(object, ...)

## S3 method for class 'sm'
deviance(object, ...)

## S3 method for class 'ss'
deviance(object, ...)

Arguments

object	an object of class "gsm" output by the gsm function, "sm" output by the sm function, or "ss" output by the ss function
...	other arugments (currently ignored)

Details

For ss and sm objects, the deviance is caculated assuming iid Gaussian errors.

For gsm objects, the deviance is calculated by summing the squared deviance residuals, which are calculated using family(object)$dev.resid

Value

Deviance of the model object.

Author(s)

Nathaniel E. Helwig <[e-mail]>

References

Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.

Helwig, N. E. (2020). Multiple and Generalized Nonparametric Regression. In P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug, & R. A. Williams (Eds.), SAGE Research Methods Foundations. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.4135/9781526421036885885")}

See Also

ss, sm, gsm

fitted.values and residuals

Examples

## for 'ss' and 'sm' objects, this function is defined as
function(object, ...){
    sum(weighted.residuals(object)^2, na.rm = TRUE)
  }
  
## for 'gsm' objects, this function is defined as
function(object, ...){
    object$deviance
  }

npreg documentation built on May 29, 2024, 4:17 a.m.