predict.scope

Computes SCOPE predictions on new data.

Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.

Daniel Grose

CatReg

Solution Paths for Linear and Logistic Regression Models with
Categorical Predictors, with SCOPE Penalty

Benjamin Stokell

Rajen Shah

predict.scope function

<dl><dt>object</dt>
<dd>SCOPE model as outputted by scope. Must have simply.the.best = TRUE</dd>
<dt>newdata</dt>
<dd>New covariates on which to make predictions. Must be of the same form as the model was trained on</dd>
<dt>include_intercept</dt>
<dd>If TRUE, a column of 1s will be added to the (continuous) design matrix. Must match format of training data.</dd>
<dt>...</dt>
<dd>Additional arguments to pass to other <code>predict</code> methods</dd></dl>

Arguments

Computes SCOPE predictions — predict.scope

<dl>

<dt>object</dt>
<dd>SCOPE model as outputted by scope. Must have simply.the.best = TRUE</dd>


<dt>newdata</dt>
<dd>New covariates on which to make predictions. Must be of the same form as the model was trained on</dd>


<dt>include_intercept</dt>
<dd>If TRUE, a column of 1s will be added to the (continuous) design matrix. Must match format of training data.</dd>


<dt>...</dt>
<dd>Additional arguments to pass to other <code>predict</code> methods</dd>

</dl>

predict.scope: Computes SCOPE predictions

Description

Usage

Value

Arguments

See Also