predict.snr: Predict Method from a Semiparametric Nonlinear Regression...

In catherinewang1/assist: A Suite of R Functions Implementing Spline Smoothing Techniques

Description

The predictions on a semiparametric nonlinear regression model object are obtained by substituting the unknwon functions together with unknown parameters with their estimates and evaluating the regression functional based on provided or default covariate values.

Usage

## S3 method for class 'snr'
predict(object, newdata, ...)

Arguments

object	a fitted snr object.
newdata	a data frame containing the values at which predictions are required. Default are NULL, where data used to produce the fit are to be taken.
...	other arguments, but currently unused.

Details

This function is a method for the generic function predict for class snr

Value

a vector of prediction values, obtained by evaluating the model in the frame newdata.

Author(s)

Chunlei Ke chunlei\[e-mail] and Yuedong Wang [e-mail]

References

Wahba, G. (1990). Spline Models for Observational Data. SIAM, Vol. 59.

Ke, C. (2000). Semi-parametric Nonlinear Regression and Mixed Effects Models. PhD thesis, University of California, Santa Barbara.

See Also

snr

catherinewang1/assist documentation built on June 16, 2019, 1:36 p.m.