predict,fitode-method

Computes estimated trajectories and their confidence intervals (using either
the delta method or importance sampling).

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

predict,fitode-method function

<dl><dt>object</dt>
<dd>fitode object</dd>
<dt>level</dt>
<dd>the confidence level required</dd>
<dt>times</dt>
<dd>time vector to predict over. Default is set to the time frame of the data.</dd>
<dt>method</dt>
<dd>confidence interval method. Default is set to Delta method.</dd>
<dt>nsim</dt>
<dd>number of simulations for mvrnorm, wmvrnorm methods</dd></dl>

Arguments

Prediction function for fitode objects — predict,fitode-method

<dl>

<dt>object</dt>
<dd>fitode object</dd>


<dt>level</dt>
<dd>the confidence level required</dd>


<dt>times</dt>
<dd>time vector to predict over. Default is set to the time frame of the data.</dd>


<dt>method</dt>
<dd>confidence interval method. Default is set to Delta method.</dd>


<dt>nsim</dt>
<dd>number of simulations for mvrnorm, wmvrnorm methods</dd>

</dl>

predict,fitode-method: Prediction function for fitode objects

Description

Usage

Value

Arguments