R: Delay Differential Equations

dde.model {scaRabee}

R Documentation

Delay Differential Equations

Description

dde.model is the system evaluation function called when a $DDE block is detected in the model file, indicating that the model is defined by delay differential equations. dde.model is typically not called directly by users

Usage

  dde.model(parms = NULL,
            derparms = NULL,
            code = NULL,
            bolus = NULL,
            infusion = NULL,
            xdata = NULL,
            covdata = NULL,
            issim = 0,
            check = FALSE,
            options = list(method='lsoda'))

Arguments

`parms`	A vector of primary parameters.
`derparms`	A list of derived parameters, specified in the $DERIVED block of code.
`code`	A list of R code extracted from the model file. Depending on content of the model file, the levels of this list could be: template, derived, lags, ode, dde, output, variance, and/or secondary.
`bolus`	A data.frame providing the instantaneous inputs entering the system of delay differential equations for the treatment and individual being evaluated.
`infusion`	A data.frame providing the zero-order inputs entering the system of delay differential equations for the treatment and individual being evaluated.
`xdata`	A vector of times at which the system is being evaluated.
`covdata`	A data.frame of covariate data for the treatment and individual being evaluated.
`issim`	An indicator for simulation or estimation runs.
`check`	An indicator whether checks should be performed to validate function inputs.
`options`	A list of delay differential equation solver options. Currently not modifiable by users.

Details

dde.model evaluates the model for each treatment of each individual contained in the dataset using, among other, the dedicated utility functions: dde.syst, and dde.lags. The actual evaluation of the system is performed by dede from the deSolve package.

dde.model also make use of utility functions which it shares with the other system evaluation functions explicit.model, and ode.model, such as create.intervals, derived.parms, init.cond, input.scaling, make.dosing, init.update, and de.output.

Value

Returns a matrix of system predictions.

Author(s)

Sebastien Bihorel (sb.pmlab@gmail.com)