create_kernel_functions

Create kernel functions based on configuration

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

create_kernel_functions function

<dl><dt>kernel.fun</dt>
<dd>A string specifying the kernel function to be used.</dd>
<dt>if_approx_kernel</dt>
<dd>Logical. If TRUE, uses approximations for the kernel function.</dd>
<dt>kernel.resol</dt>
<dd>The resolution for kernel function approximation.</dd></dl>

Arguments

Create kernel functions based on configuration — create_kernel_functions

<dl>

<dt>kernel.fun</dt>
<dd>A string specifying the kernel function to be used.</dd>


<dt>if_approx_kernel</dt>
<dd>Logical. If TRUE, uses approximations for the kernel function.</dd>


<dt>kernel.resol</dt>
<dd>The resolution for kernel function approximation.</dd>

</dl>

create_kernel_functions: Create kernel functions based on configuration

Description

Usage

Value

Arguments