grad,loglik.ode-method

Evaluate the gradient of a likelihood model

internal

Methods and functions for fitting ordinary differential equations (ODE) model in 'R'. Sensitivity equations are used to compute the gradients of ODE trajectories with respect to underlying parameters, which in turn allows for more stable fitting. Other fitting methods, such as MCMC (Markov chain Monte Carlo), are also available.

Sang Woo Park

fitode

Tools for Ordinary Differential Equations Model Fitting

Ben Bolker

grad,loglik.ode-method function

<dl><dt>object</dt>
<dd>loglik.ode object</dd>
<dt>observation</dt>
<dd>observations</dd>
<dt>mean</dt>
<dd>mean values</dd>
<dt>par</dt>
<dd>additional parameters</dd>
<dt>...</dt>
<dd>other values if required</dd></dl>

Arguments

Evaluate the gradient of a likelihood model — grad,loglik.ode-method

<dl>

<dt>object</dt>
<dd>loglik.ode object</dd>


<dt>observation</dt>
<dd>observations</dd>


<dt>mean</dt>
<dd>mean values</dd>


<dt>par</dt>
<dd>additional parameters</dd>


<dt>...</dt>
<dd>other values if required</dd>

</dl>

grad,loglik.ode-method: Evaluate the gradient of a likelihood model

Description

Usage

Value

Arguments