Improved Asymptotics for Zeros of Kernel Estimates via a Reformulation of the Leadbetter-Cryer Integral

03/11/2018
by   Kurt S. Riedel, et al.
0

The expected number of false inflection points of kernel smoothers is evaluated. To obtain the small noise limit, we use a reformulation of the Leadbetter-Cryer integral for the expected number of zero crossings of a differentiable Gaussian process.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/04/2019

Deep kernel learning for integral measurements

Deep kernel learning refers to a Gaussian process that incorporates neur...
research
08/07/2017

Multiresolution Kernel Approximation for Gaussian Process Regression

Gaussian process regression generally does not scale to beyond a few tho...
research
09/10/2021

On the eigenvalues associated with the limit null distribution of the Epps-Pulley test of normality

The Shapiro–Wilk test (SW) and the Anderson–Darling test (AD) turned out...
research
08/27/2019

Separability of the kernel function in an integral formulation for anisotropic radiative transfer equation

We study in this work an integral formulation for the radiative transfer...
research
03/11/2023

Characterizations of the set of integer points in an integral bisubmodular polyhedron

In this note, we provide two characterizations of the set of integer poi...
research
12/17/2021

Gaussian RBF Centered Kernel Alignment (CKA) in the Large Bandwidth Limit

We prove that Centered Kernel Alignment (CKA) based on a Gaussian RBF ke...
research
09/18/2023

The Kernel Density Integral Transformation

Feature preprocessing continues to play a critical role when applying ma...

Please sign up or login with your details

Forgot password? Click here to reset