summary.ldt.search.item

While you can get a summary of an item in a search result, this function is mainly designed to be called from print.ldt.search function.
Its main job is to estimate the full model using the reported indices from the search process.

Methods and tools for model selection and multi-model inference (Burnham and Anderson (2002) <doi:10.1007/b97636>, among others).
'SUR' (for parameter estimation), 'logit'/'probit' (for binary classification), and 'VARMA' (for time-series forecasting) are implemented.
Evaluations are both in-sample and out-of-sample.
It is designed to be efficient in terms of CPU usage and memory consumption.

Ramin Mojab

Automated Uncertainty Analysis

Stephen Becker

summary.ldt.search.item function

<dl><dt>object</dt>
<dd>An <code>ldt.search.item</code> object.</dd>
<dt>searchResult</dt>
<dd>Parent list of <code>object</code>, which is an <code>ldt.search</code> object.</dd>
<dt>test</dt>
<dd>If <code>TRUE</code> and applicable (e.g., in model estimation), it checks the metrics and throws error for any inconsistencies between the current estimation and the one calculated in the search process.</dd>
<dt>...</dt>
<dd>Additional arguments.</dd></dl>

Arguments

Summary for an ldt.search.item object — summary.ldt.search.item

<dl>

<dt>object</dt>
<dd>An <code>ldt.search.item</code> object.</dd>


<dt>searchResult</dt>
<dd>Parent list of <code>object</code>, which is an <code>ldt.search</code> object.</dd>


<dt>test</dt>
<dd>If <code>TRUE</code> and applicable (e.g., in model estimation), it checks the metrics and throws error for any inconsistencies between the current estimation and the one calculated in the search process.</dd>


<dt>...</dt>
<dd>Additional arguments.</dd>

</dl>

summary.ldt.search.item: Summary for an `ldt.search.item` object

Description

Usage

Value

Arguments

Details