Define compiled code for ordinary differential equation.

specify_ode(code, fname = NULL, pname = c("dy", "x", "y", "p"))

## Arguments

code

string with the body of the function definition (see details)

fname

Optional name of the exported C++ function

pname

Vector of variable names (results, inputs, states, parameters)

## Value

pointer (externalptr) to C++ function

## Details

The model (code) should be specified as the body of of C++ function. The following variables are defined bye default (see the argument pname)

dy

Vector with derivatives, i.e. the rhs of the ODE (the result).

x

Vector with the first element being the time, and the following elements additional exogenous input variables,

y

Vector with the dependent variable

p

Parameter vector

$$y'(t) = f_{p}(x(t), y(t))$$ All variables are treated as Armadillo (http://arma.sourceforge.net/) vectors/matrices.

As an example consider the Lorenz Equations $$\frac{dx_{t}}{dt} = \sigma(y_{t}-x_{t})$$ $$\frac{dy_{t}}{dt} = x_{t}(\rho-z_{t})-y_{t}$$ $$\frac{dz_{t}}{dt} = x_{t}y_{t}-\beta z_{t}$$

We can specify this model as ode <- 'dy(0) = p(0)*(y(1)-y(0)); dy(1) = y(0)*(p(1)-y(2)); dy(2) = y(0)*y(1)-p(2)*y(2);' dy <- specify_ode(ode)

As an example of model with exogenous inputs consider the following ODE: $$y'(t) = \beta_{0} + \beta_{1}y(t) + \beta_{2}y(t)x(t) + \beta_{3}x(t)\cdot t$$ This could be specified as mod <- 'double t = x(0); dy = p(0) + p(1)*y + p(2)*x(1)*y + p(3)*x(1)*t;' dy <- specify_ode(mod)##'