predict.cggd {cggd} | R Documentation

## Make predictions or extract coefficients from a fitted cggd model

### 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)

[Package cggd version 0.8 Index]