Description Usage Arguments Details Value See Also Examples
View source: R/fitted.l2boost.R
fitted
is a generic function which extracts fitted values from objects
returned by modeling functions.
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object |
an l2boost object |
m |
the iteration number with the l2boost path. (default m=NULL) |
... |
other arguments |
fitted.l2boost
returns the function estimates obtained
from the training set observations of an l2boost model object at any point along the solution path.
The estimate, F_m(x) is evaluated at iteration m using the training data set x. By default,
fitted.l2boost
returns the estimate at the last iteration step M, unless a specific
iteration step m is specified.
The vector of fitted response estimates at the given iteration m. By default, the coefficients are obtained from the last iteration m=M.
fitted
and l2boost
and predict.l2boost
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# Example: Diabetes
#
# See Efron B., Hastie T., Johnstone I., and Tibshirani R.
# Least angle regression. Ann. Statist., 32:407-499, 2004.
data(diabetes, package="l2boost")
l2.object <- l2boost(diabetes$x,diabetes$y, M=1000, nu=.01)
# return the fitted values
fitted(l2.object)
fitted(l2.object, m=500)
#' # Create diagnostic plots
par(mfrow=c(2,2))
qqnorm(fitted(l2.object), ylim=c(0, 300))
qqline(fitted(l2.object), col=2)
qqnorm(fitted(l2.object, m=500), ylim=c(0, 300))
qqline(fitted(l2.object, m=500), col=2)
# Tukey-Anscombe's plot
plot(y=residuals(l2.object), x=fitted(l2.object), main="Tukey-Anscombe's plot",
ylim=c(-3e-13, 3e-13))
lines(smooth.spline(fitted(l2.object), residuals(l2.object), df=4), type="l",
lty=2, col="red", lwd=2)
abline(h=0, lty=2, col = 'gray')
plot(y=residuals(l2.object, m=500), x=fitted(l2.object, m=500),
main="Tukey-Anscombe's plot", ylim=c(-3e-13, 3e-13))
lines(smooth.spline(fitted(l2.object,m=500), residuals(l2.object, m=500), df=4),
type="l", lty=2, col="red", lwd=2)
abline(h=0, lty=2, col = 'gray')
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