| fitted.KernS | Methods for ("KernS" classed) Results of lokerns() and glkerns() |
| glkerns | Kernel Regression Smoothing with Adaptive Plug-in Bandwidth |
| glkerns.default | Kernel Regression Smoothing with Adaptive Plug-in Bandwidth |
| glkerns.formula | Kernel Regression Smoothing with Adaptive Plug-in Bandwidth |
| lines.KernS | Methods for ("KernS" classed) Results of lokerns() and glkerns() |
| lokerns | Kernel Regression Smoothing with Local Plug-in Bandwidth |
| lokerns.default | Kernel Regression Smoothing with Local Plug-in Bandwidth |
| lokerns.formula | Kernel Regression Smoothing with Local Plug-in Bandwidth |
| plot.KernS | Methods for ("KernS" classed) Results of lokerns() and glkerns() |
| predict.KernS | Methods for ("KernS" classed) Results of lokerns() and glkerns() |
| print.KernS | Methods for ("KernS" classed) Results of lokerns() and glkerns() |
| residuals.KernS | Methods for ("KernS" classed) Results of lokerns() and glkerns() |
| varest | Nonparametric Variance Estimator |
| varNPreg | Nonparametric Variance Estimator |
| xSim | Simulated Linear plus Exponential Peak |