estim.binary.model.string

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

estim.binary.model.string function

<dl><dt>object</dt>
<dd>A <code>estim.bin</code> object</dd></dl>

Arguments

Get Model Name — estim.binary.model.string

<dl>

<dt>object</dt>
<dd>A <code>estim.bin</code> object</dd>

</dl>

estim.binary.model.string: Get Model Name

Description

Usage

Value

Arguments