Computing the OSCV smooth rescaling constant that corresponds to using the two-sided kernel
H_I for the cross-validation purposes and the Gaussian kernel in the estimation stage. The constant is applicable for the OSCV versions in the regression and kernel density estimation contexts.
first parameter of the two-sided cross-validation kernel
second parameter of the two-sided cross-validation kernel
Computation of the OSCV rescaling constant C (see (10) in Savchuk and Hart (2017) or (3) in Savchuk (2017)). The constant is a function of the parameters (α,σ) of the two-sided cross-validation kernel
H_I defined by expression (15) in Savchuk and Hart (2017). The Gaussian kernel is used for computing the ultimate (regression or density) estimate. The constant is used in the OSCV versions for kernel regression and density estimation. Notice that in the cases α=0, σ>0 and σ=1, -∞<α<∞ the kernel
H_I reduces to the Gaussian kernel.
The OSCV smooth rescaling constant C for the given values of the parameters α and σ.
Savchuk, O.Y., Hart, J.D. (2017). Fully robust one-sided cross-validation for regression functions. Computational Statistics, doi:10.1007/s00180-017-0713-7.
Savchuk, O.Y. (2017). One-sided cross-validation for nonsmooth density functions, arXiv:1703.05157.
1 2 3 4 5
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.