predict.MADMMplasso

Compute predicted values from a MADMMplasso object.
Make predictions from a fitted MADMMplasso model

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

predict.MADMMplasso function

<dl><dt>object</dt>
<dd>object returned from a call to MADMMplasso</dd>
<dt>X</dt>
<dd>N by p matrix of predictors</dd>
<dt>Z</dt>
<dd>N by nz matrix of modifying variables. These may be observed or
the predictions from a supervised learning algorithm that predicts z from
test features x and possibly other features.</dd>
<dt>y</dt>
<dd>N by D matrix of responses.</dd>
<dt>lambda</dt>
<dd>values of lambda at which predictions are desired. If NULL (default), the path of lambda values from the fitted model. are used. If lambda is not NULL, the predictions are made at the closest values to lambda in the lambda path from the fitted model</dd>
<dt>...</dt>
<dd>additional arguments to the generic <code><a href="/link/predict()?package=MADMMplasso&version=1.0.1" data-mini-rdoc="MADMMplasso::predict()">predict()</a></code> method</dd></dl>

Arguments

Compute predicted values from a fitted MADMMplasso  object.
Make predictions from a fitted MADMMplasso model — predict.MADMMplasso

<dl>

<dt>object</dt>
<dd>object returned from a call to MADMMplasso</dd>


<dt>X</dt>
<dd>N by p matrix of predictors</dd>


<dt>Z</dt>
<dd>N by nz matrix of modifying variables. These may be observed or
the predictions from a supervised learning algorithm that predicts z from
test features x and possibly other features.</dd>


<dt>y</dt>
<dd>N by D matrix of responses.</dd>


<dt>lambda</dt>
<dd>values of lambda at which predictions are desired. If NULL (default), the path of lambda values from the fitted model. are used. If lambda is not NULL, the predictions are made at the closest values to lambda in the lambda path from the fitted model</dd>


<dt>...</dt>
<dd>additional arguments to the generic <code><a href='https://rdrr.io/r/stats/predict.html'>predict()</a></code> method</dd>

</dl>

predict.MADMMplasso: Compute predicted values from a fitted MADMMplasso object. Make predictions from a fitted MADMMplasso model

Description

Usage

Value

Arguments