Loading...
Please wait, while we are loading the content...
Similar Documents
Locally-based kernal pls smoothing to non-parametric regression curve fitting
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Trejo, Leonard J. Rosipal, Roman Wheeler, Kevin |
| Copyright Year | 2002 |
| Description | We present a novel smoothing approach to non-parametric regression curve fitting. This is based on kernel partial least squares (PLS) regression in reproducing kernel Hilbert space. It is our concern to apply the methodology for smoothing experimental data where some level of knowledge about the approximate shape, local inhomogeneities or points where the desired function changes its curvature is known a priori or can be derived based on the observed noisy data. We propose locally-based kernel PLS regression that extends the previous kernel PLS methodology by incorporating this knowledge. We compare our approach with existing smoothing splines, hybrid adaptive splines and wavelet shrinkage techniques on two generated data sets. |
| File Size | 2047201 |
| Page Count | 36 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20030015244 |
| Archival Resource Key | ark:/13960/t76t5mn2p |
| Language | English |
| Publisher Date | 2002-01-01 |
| Access Restriction | Open |
| Subject Keyword | Numerical Analysis Kernel Functions Least Squares Method Noise Reduction Signal Processing Wavelet Analysis Mathematical Models Applications Programs Computers Computerized Simulation Regression Analysis Functions Mathematics Data Smoothing Curve Fitting Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
