6.5.6.2.7. statsmodels.sandbox.nonparametric.kernels.NdKernel

class statsmodels.sandbox.nonparametric.kernels.NdKernel(n, kernels=None, H=None)

Generic N-dimensial kernel

Parameters:

n : int

The number of series for kernel estimates

kernels : list

kernels

Can be constructed from either

a) a list of n kernels which will be treated as

indepent marginals on a gaussian copula (specified by H)

or b) a single univariate kernel which will be applied radially to the

mahalanobis distance defined by H.

In the case of the Gaussian these are both equivalent, and the second constructiong

is prefered.

__init__(n, kernels=None, H=None)

6.5.6.2.7.1. Methods

__init__(n[, kernels, H])
density(xs, x)
getH()	Getter for kernel bandwidth, H
setH(value)	Setter for kernel bandwidth, H

6.5.6.2.7.2. Attributes

H	Kernel bandwidth matrix