bw_rot

internal

Tools for estimation and inference of conditional densities, derivatives and functions. This is the companion software for Cattaneo, Chandak, Jansson and Ma (2024) <doi:10.3150/23-BEJ1711>.

Rajita Chandak

lpcde

Boundary Adaptive Local Polynomial Conditional Density Estimator

Michael Jansson

Xinwei Ma

bw_rot function

<dl><dt>y_data</dt>
<dd>Numeric matrix/data frame, the raw data of independent.</dd>
<dt>x_data</dt>
<dd>Numeric matrix/data frame, the raw data of covariates.</dd>
<dt>y_grid</dt>
<dd>Numeric vector, the evaluation points.</dd>
<dt>x</dt>
<dd>Numeric, specifies the evaluation point(s) in the x-direction.</dd>
<dt>p</dt>
<dd>Integer, polynomial order.</dd>
<dt>q</dt>
<dd>Integer, polynomial order.</dd>
<dt>mu</dt>
<dd>Integer, order of derivative.</dd>
<dt>nu</dt>
<dd>Integer, order of derivative.</dd>
<dt>kernel_type</dt>
<dd>String, the kernel.</dd>
<dt>regularize</dt>
<dd>Boolean.</dd></dl>

Arguments

ROT Bandwidth selection — bw_rot

<dl>

<dt>y_data</dt>
<dd>Numeric matrix/data frame, the raw data of independent.</dd>


<dt>x_data</dt>
<dd>Numeric matrix/data frame, the raw data of covariates.</dd>


<dt>y_grid</dt>
<dd>Numeric vector, the evaluation points.</dd>


<dt>x</dt>
<dd>Numeric, specifies the evaluation point(s) in the x-direction.</dd>


<dt>p</dt>
<dd>Integer, polynomial order.</dd>


<dt>q</dt>
<dd>Integer, polynomial order.</dd>


<dt>mu</dt>
<dd>Integer, order of derivative.</dd>


<dt>nu</dt>
<dd>Integer, order of derivative.</dd>


<dt>kernel_type</dt>
<dd>String, the kernel.</dd>


<dt>regularize</dt>
<dd>Boolean.</dd>

</dl>

bw_rot: ROT Bandwidth selection

Description

Usage

Value

Arguments