predict.ibr {ibr} | R Documentation |
Predicted values using iterative bias reduction smoothers
Description
Predicted values from iterative bias reduction object.
Missing values are not allowed.
Usage
## S3 method for class 'ibr'
predict(object, newdata, interval=
c("none", "confidence", "prediction"), ...)
Arguments
object |
Object of class |
newdata |
An optional matrix in which to look for variables with which to predict. If omitted, the fitted values are used. |
interval |
Type of interval calculation. Only |
... |
Further arguments passed to or from other methods. |
Value
Produces a vector of predictions.
Author(s)
Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.
References
Cornillon, P.-A.; Hengartner, N.; Jegou, N. and Matzner-Lober, E. (2012) Iterative bias reduction: a comparative study. Statistics and Computing, 23, 777-791.
Cornillon, P.-A.; Hengartner, N. and Matzner-Lober, E. (2013) Recursive bias estimation for multivariate regression smoothers Recursive bias estimation for multivariate regression smoothers. ESAIM: Probability and Statistics, 18, 483-502.
Cornillon, P.-A.; Hengartner, N. and Matzner-Lober, E. (2017) Iterative Bias Reduction Multivariate Smoothing in R: The ibr Package. Journal of Statistical Software, 77, 1–26.
See Also
Examples
## Not run: data(ozone, package = "ibr")
res.ibr <- ibr(ozone[,-1],ozone[,1],df=1.2,K=1:500)
summary(res.ibr)
predict(res.ibr)
## End(Not run)