get.options.newton

Use this function to get optimization options in estim.bin or search.bin functions.

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

get.options.newton function

<dl><dt>maxIterations</dt>
<dd>An integer representing the maximum number of iterations.</dd>
<dt>functionTol</dt>
<dd>A small value used to test the convergence of the objective function.</dd>
<dt>gradientTol</dt>
<dd>A small value used to test the convergence of the gradient.</dd>
<dt>useLineSearch</dt>
<dd>If <code>TRUE</code>, line search is used.</dd></dl>

Arguments

Get Options for Newton Optimization — get.options.newton

<dl>

<dt>maxIterations</dt>
<dd>An integer representing the maximum number of iterations.</dd>


<dt>functionTol</dt>
<dd>A small value used to test the convergence of the objective function.</dd>


<dt>gradientTol</dt>
<dd>A small value used to test the convergence of the gradient.</dd>


<dt>useLineSearch</dt>
<dd>If <code>TRUE</code>, line search is used.</dd>

</dl>

get.options.newton: Get Options for Newton Optimization

Description

Usage

Value

Arguments