predict.cggd: Make predictions or extract coefficients from a fitted cggd...

In cggd: Continuous Generalized Gradient Descent

Description

While cggd produces the entire path of solutions, predict.cggd allows one to extract a prediction at a particular point along the path.

Usage

 ## S3 method for class 'cggd'
predict(object, newx, t, type = c("fit", "coefficients"), mode=c("k","t"), ...)

Arguments

object	A fitted cggd object
newx	If type="fit", then newx should be the x values at which the fit is required. If type="coefficients", then newx can be omitted.
t	A value specifying the desired model. Its values depends on the mode argument. By default (mode="k"), t should take on values between 0 and max k (e.g., a step of 1.3 means .3 of the way between step 1 and 2.)
type	If type="fit", predict returns the fitted value. If type="coefficients", predict returns the coefficients.
mode	Mode="k" means the t= argument indexes the cggd step number, and the coefficients will be returned corresponding to the values at step t. If mode="t", then t is a time on the coefficient path.
...	additional parameters.

Value

Either the fitted value, or a vector of coefficients.

Author(s)

Cun-Hui Zhang and Ofer Melnik

References

Cun-Hui Zhang (2007) "Continuous Generalized Gradient Descent" Journal of Computational and Graphical Statistics ; see also http://stat.rutgers.edu/~cunhui/software/CGGD.html.

See Also

plot, cggd, cv.cggd

Examples

data(housing)
attach(housing)
object <- cggd(x,y)
coef4.1 <- predict(object, t=4.1,type="coefficients", mode="k") 
detach(housing)

cggd documentation built on May 30, 2017, 4:33 a.m.