W_kernel_ft

Define the Fourier transform of a infinite kernel proposed in Schennach 2004

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_ft function

<dl><dt>xi</dt>
<dd>A numerical value or vector representing the frequency domain.</dd>
<dt>xi_lb</dt>
<dd>The lower bound for the frequency domain. Defaults to 0.5.</dd>
<dt>xi_ub</dt>
<dd>The upper bound for the frequency domain. Defaults to 1.5.</dd></dl>

Arguments

Define the Fourier transform of a infinite kernel proposed in Schennach 2004 — W_kernel_ft

<dl>

<dt>xi</dt>
<dd>A numerical value or vector representing the frequency domain.</dd>


<dt>xi_lb</dt>
<dd>The lower bound for the frequency domain. Defaults to 0.5.</dd>


<dt>xi_ub</dt>
<dd>The upper bound for the frequency domain. Defaults to 1.5.</dd>

</dl>

W_kernel_ft: Define the Fourier transform of a infinite kernel proposed in Schennach 2004

Description

Usage

Value

Arguments