6.5.6. statsmodels.sandbox.nonparametric.kernels¶
This models contains the Kernels for Kernel smoothing.
Hopefully in the future they may be reused/extended for other kernel based method
6.5.6.1. References:¶
Pointwise Kernel Confidence Bounds (smoothconf) http://fedc.wiwi.hu-berlin.de/xplore/ebooks/html/anr/anrhtmlframe62.html
6.5.6.2. Classes¶
Biweight([h]) |
|
Cosine([h]) |
Cosine Kernel |
Cosine2([h]) |
Cosine2 Kernel |
CustomKernel(shape[, h, domain, norm]) |
Generic 1D Kernel object. |
Epanechnikov([h]) |
|
Gaussian([h]) |
Gaussian (Normal) Kernel |
NdKernel(n[, kernels, H]) |
Generic N-dimensial kernel |
Triangular([h]) |
|
Triweight([h]) |
|
Uniform([h]) |