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copied!<p>If the simulation function always takes the same set of arguments, then Ramnath's approach of storing them in a data frame is best. For the more general case of variable inputs to <code>mySimulation</code>, you should store each set of inputs in a list – probably using a list of lists for running several simluations.</p> <p>The idea behind your <code>createParms</code> function looks sound; you can simplify the code a little bit.</p> <pre><code>createParms <- function(model = "default", ...) { #default case parms <- list( parm1 = 0, parm2 = 0 ) #other special cases if(model == "mymodel") { parms <- within(parms, { parm1 <- 1 parm2 <- 2 }) } #overwrite from ... dots <- list(...) parms[names(dots)] <- dots parms } </code></pre> <p>Test this with, e.g.,</p> <pre><code>createParms() createParms("mymodel") createParms("mymodel", parm2 = 3) </code></pre> <p><code>do.call</code> may come in handy for running your simulation, as in</p> <pre><code>do.call(mySimulation, createParms()) </code></pre> <hr> <p>EDIT: What <code>do.call</code> does for you</p> <p>If you have <code>parms <- createParms()</code>, then </p> <pre><code>do.call(mySimulation, parms) </code></pre> <p>is the same as</p> <pre><code>with(parms, mySimulation(parm1, parm2)) </code></pre> <p>The main advantage is that you don't need to spell out each parameter that you are passing into <code>mySimulation</code> (or to modify that function to accept the parameters in list form).</p>

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