simulate_internal

Simulates deterministic trajectories and propagates observation error

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

simulate_internal function

<dl><dt>model</dt>
<dd>odemodel object</dd>
<dt>times</dt>
<dd>time vector</dd>
<dt>parms</dt>
<dd>named vector of parameter values</dd>
<dt>y</dt>
<dd>initial values</dd>
<dt>solver.opts</dt>
<dd>options for ode solver</dd>
<dt>solver</dt>
<dd>ode solver (must take y, times, func, and parms arguments)</dd>
<dt>observation</dt>
<dd>(logical) propagate observation error?</dd>
<dt>nsim</dt>
<dd>number of simulations</dd>
<dt>seed</dt>
<dd>seed</dd></dl>

Arguments

Internal function for simulation models — simulate_internal

<dl>

<dt>model</dt>
<dd>odemodel object</dd>


<dt>times</dt>
<dd>time vector</dd>


<dt>parms</dt>
<dd>named vector of parameter values</dd>


<dt>y</dt>
<dd>initial values</dd>


<dt>solver.opts</dt>
<dd>options for ode solver</dd>


<dt>solver</dt>
<dd>ode solver (must take y, times, func, and parms arguments)</dd>


<dt>observation</dt>
<dd>(logical) propagate observation error?</dd>


<dt>nsim</dt>
<dd>number of simulations</dd>


<dt>seed</dt>
<dd>seed</dd>

</dl>

simulate_internal: Internal function for simulation models

Description

Usage

Arguments