MParzenTest: Testing MParzen model

In rudazhang/plmr: Probabilistic Learning on Manifolds in R

Description

Modified to add noise level \min(σ, s_d) to the normal directions, instead of adding σ^2 to all directions.

Usage

MParzenTest(y, X, model, sigma)

Arguments

y	density evaluation point.
X	matrix of training data.
model	Top d-th order local covariance structure; output of 'MParzenTrain()'.
sigma	Maximum noise level added to the normal space of each kernel, i.e. marginal standard deviation of an isotropic Gaussian. Should be greater than zero.

Value

Manifold Parzen estimator at the evaluation point.

References

@Vincent2002

rudazhang/plmr documentation built on Aug. 30, 2021, 5:43 p.m.