predict.snr: Predict Method from a Semiparametric Nonlinear Regression Model Fit
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
predict.snr(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.
Value
a vector of prediction values, obtained by evaluating the model in the frame newdata.
Details
This function is a method for the generic function predict for class snr
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.