npreg (version 1.0-8)

fitted: Extract Model Fitted Values

Description

Extracts the fitted values from a fit smoothing spline ("ss"), smooth model ("sm"), or generalized smooth model ("gsm") object.

Usage

# S3 method for ss
fitted(object, ...)
# S3 method for ss
fitted.values(object, ...)
# S3 method for sm
fitted(object, ...)
# S3 method for sm
fitted.values(object, ...)
# S3 method for gsm
fitted(object, ...)
# S3 method for gsm
fitted.values(object, ...)

Value

Fitted values extracted (or predicted) from object

Arguments

object

an object of class "ss", "sm", or "gsm"

...

other arugments (currently ignored)

Author

Nathaniel E. Helwig <[e-mail]>

Details

For objects of class ss, fitted values are predicted via predict(object, object$data$x)$y

For objects of class sm, fitted values are extracted via object$fitted.values

For objects of class gsm, fitted values are computed via ginv(object$linear.predictors) where ginv = object$family$linkinv

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. tools:::Rd_expr_doi("10.4135/9781526421036885885")

See Also

ss, sm, gsm

Examples

# generate data
set.seed(1)
n <- 100
x <- seq(0, 1, length.out = n)
fx <- 2 + 3 * x + sin(2 * pi * x)
y <- fx + rnorm(n, sd = 0.5)

# smoothing spline
mod.ss <- ss(x, y, nknots = 10)
fit.ss <- fitted(mod.ss)

# smooth model
mod.sm <- sm(y ~ x, knots = 10)
fit.sm <- fitted(mod.sm)

# generalized smooth model (family = gaussian)
mod.gsm <- gsm(y ~ x, knots = 10)
fit.gsm <- fitted(mod.gsm)

# compare fitted values
mean((fit.ss - fit.sm)^2)
mean((fit.ss - fit.gsm)^2)
mean((fit.sm - fit.gsm)^2)