W_kernel

Define the inverse Fourier transform function of W

A novel bias-bound approach for non-parametric inference is introduced,
focusing on both density and conditional expectation estimation.
It constructs valid confidence intervals that account for the presence of
a non-negligible bias and thus make it possible to perform inference with
optimal mean squared error minimizing bandwidths.
This package is based on Schennach (2020) <doi:10.1093/restud/rdz065>.

Xinyu DAI

rbbnp

A Bias Bound Approach to Non-Parametric Inference

Susanne M Schennach

W_kernel function

<dl><dt>u</dt>
<dd>A numerical value or vector representing the time or space domain.</dd>
<dt>L</dt>
<dd>The limit for numerical integration, defines the range of integration as \([-L, L]\).
Defaults to 10.</dd></dl>

Arguments

Define the inverse Fourier transform function of W — W_kernel

<dl>

<dt>u</dt>
<dd>A numerical value or vector representing the time or space domain.</dd>


<dt>L</dt>
<dd>The limit for numerical integration, defines the range of integration as \([-L, L]\).
Defaults to 10.</dd>

</dl>

W_kernel: Define the inverse Fourier transform function of W

Description

Usage

Value

Arguments