(1) Introduction to MCSimMod"

In MCSimMod: Working with 'MCSim' Models

knitr::opts_chunk$set(
  echo = TRUE,
  warning = FALSE,
  collapse = TRUE,
  comment = "#>"
)

The MCSimMod package can be used to define ordinary differential equation (ODE) models and solve initial value problems (IVPs) for such models. To define an ODE model, one first creates a "model specification" as a text string or a text file. (More details about the structure of the model specification text are provided in a separate vignette: "Model Specification".) The model specification text can then be used to create a model object (i.e., an instance of the MCSimMod Model class) via the MCSimMod function createModel().

Consider, for example, a simple ODE model given by \begin{align} \frac{\textrm{d}}{\textrm{d}t}y(t) &= m, \ y(0) &= y_0. \end{align} We can create a model object corresponding to this ODE model using a text string that both provides the ODE for the state variable, $y$, and sets the (default) values of the model parameters to $y_0 = 2$ and $m = 0.5$.

First, we load the MCSimMod package as follows.

library(MCSimMod)

Then, we define the model string as follows.

mod_string <- "
States = {y};
y0 = 2;
m = 0.5;
Initialize {
    y = y0;
}
Dynamics {
    dt(y) = m;
}
End.
"

Next, we create a Model object called model using the following command.

model <- createModel(mString = mod_string)

Once the model object is created, we can "load" the model (so that it's ready for use in a given R session) as follows.

model$loadModel()

Then, we can perform a simulation that provides results for the desired output times ($t = 0, 0.1, 0.2, \ldots, 20.0$) using the following commands.

times <- seq(from = 0, to = 20, by = 0.1)
out <- model$runModel(times)

The final command shown above performs the model simulation and stores the simulation results in a "matrix" data structure called out. The first five rows of this data structure are shown below. Note that the independent variable, which is $t$ in the case of the linear model we've created here, is always labeled "time" in the output data structure.

library(knitr)
kable(out[1:5, ])

We can examine the parameter values and initial conditions that were used for this simulation with the following commands.

model$parms
model$Y0

Finally, we can create a visual representation of the simulation results. For example, we can plot the value of $y$ vs. time ($t$) using the following command.

# Plot simulation results.
plot(out[, "time"], out[, "y"],
  type = "l", lty = 1, lwd = 2, xlab = "Time",
  ylab = "y"
)

MCSimMod documentation built on Aug. 21, 2025, 5:54 p.m.