Transform,loglik.ode-method

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

Transform,loglik.ode-method function

<dl><dt>object</dt>
<dd>loglik.ode object</dd>
<dt>transforms</dt>
<dd>list of formulas specifying transformations</dd>
<dt>name</dt>
<dd>name of the log-likelihood model</dd>
<dt>observation</dt>
<dd>observation variable name</dd>
<dt>mean</dt>
<dd>mean variable name</dd>
<dt>par</dt>
<dd>additional parameter names</dd>
<dt>keep_grad</dt>
<dd>maintain the gradient as part of the model</dd></dl>

Arguments

Transform the model — Transform,loglik.ode-method

<dl>

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


<dt>transforms</dt>
<dd>list of formulas specifying transformations</dd>


<dt>name</dt>
<dd>name of the log-likelihood model</dd>


<dt>observation</dt>
<dd>observation variable name</dd>


<dt>mean</dt>
<dd>mean variable name</dd>


<dt>par</dt>
<dd>additional parameter names</dd>


<dt>keep_grad</dt>
<dd>maintain the gradient as part of the model</dd>

</dl>

Transform,loglik.ode-method: Transform the model

Description

Usage

Value

Arguments