sim2

This system allows one to model a multi-variate, multi-response
problem with interaction effects. It combines the usual squared error loss
for the multi-response problem with some penalty terms to encourage
responses that correlate to form groups and also allow for modeling main and
interaction effects that exit within the covariates.
The optimization method employed is the Alternating Direction Method of
Multipliers (ADMM). The implementation is based on the methodology
presented on Quachie Asenso, T., & Zucknick, M. (2023)
<doi:10.48550/arXiv.2303.11155>.

Waldir Leoncio

MADMMplasso

Multi Variate Multi Response ADMM with Interaction Effects

Theophilus Quachie Asenso

Manuela Zucknick

Chi Zhang

sim2 function

<dl><dt>p</dt>
<dd>column for X which is the main effect</dd>
<dt>n</dt>
<dd>number of observations</dd>
<dt>m</dt>
<dd>number of responses</dd>
<dt>nz</dt>
<dd>number of modifiers</dd>
<dt>rho</dt>
<dd>values to be used in the covariance matrix when generating X</dd>
<dt>B.elem</dt>
<dd>the value of the non-zero elements in beta?</dd></dl>

Arguments

Simulate data for the model. This is the second simulation data used in the paper — sim2

<dl>

<dt>p</dt>
<dd>column for X which is the main effect</dd>


<dt>n</dt>
<dd>number of observations</dd>


<dt>m</dt>
<dd>number of responses</dd>


<dt>nz</dt>
<dd>number of modifiers</dd>


<dt>rho</dt>
<dd>values to be used in the covariance matrix when generating X</dd>


<dt>B.elem</dt>
<dd>the value of the non-zero elements in beta?</dd>

</dl>

sim2: Simulate data for the model. This is the second simulation data used in the paper

Description

Usage

Value

Arguments