update_beta_qr

<code>update_beta_qr</code> updates beta for L2E multivariate regression via a QR solve

An implementation of a computational framework for performing robust structured regression with the L2 criterion
from Chi and Chi (2021+). Improvements using the majorization-minimization (MM) principle from Liu, Chi, and
Lange (2022+) added in Version 2.0.

Jocelyn Chi

Robust Structured Regression via the L2 Criterion

Xiaoqian Liu

Lisa Lin

Kenneth Lange

Eric Chi

update_beta_qr function

<dl><dt>y</dt>
<dd>Response vector</dd>
<dt>X</dt>
<dd>Design matrix</dd>
<dt>QRF</dt>
<dd>QR factorization object for X (obtained via `QRF=qr(X)`)</dd>
<dt>tau</dt>
<dd>Current estimate for tau</dd>
<dt>b</dt>
<dd>Current estimate for beta</dd>
<dt>max_iter</dt>
<dd>Maximum number of iterations</dd>
<dt>tol</dt>
<dd>Relative tolerance</dd></dl>

Arguments

Beta update in L2E multivariate regression - PG — update_beta_qr

<dl>

<dt>y</dt>
<dd>Response vector</dd>


<dt>X</dt>
<dd>Design matrix</dd>


<dt>QRF</dt>
<dd>QR factorization object for X (obtained via `QRF=qr(X)`)</dd>


<dt>tau</dt>
<dd>Current estimate for tau</dd>


<dt>b</dt>
<dd>Current estimate for beta</dd>


<dt>max_iter</dt>
<dd>Maximum number of iterations</dd>


<dt>tol</dt>
<dd>Relative tolerance</dd>

</dl>

update_beta_qr: Beta update in L2E multivariate regression - PG

Description

Usage

Value

Arguments