Resistant selection of the smoothing parameter for smoothing splines
Statistics and Computing
Editorial: Special issue on variable selection and robust procedures
Computational Statistics & Data Analysis
On robust cross-validation for nonparametric smoothing
Computational Statistics
Hi-index | 0.03 |
Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. Various robust smoothing methods for estimating fluorescence emission spectra are compared and data driven methods for the selection of smoothing parameter are suggested. The methods currently implemented in R for smoothing parameter selection proved to be unsatisfactory, and a computationally efficient procedure that approximates robust leave-one-out cross validation is presented.