# Run a function iteratively, with options for parallel processing. `run_test` runs a user-defined function iteratively. This function is intentionally kept general and flexible, to allow for a wide variety of applications. This function is the general-purpose function called by functions such as `grid_search` and `random_search`, which provide different methods for generating the parameters to be tested. ```r run_test(func, params = NULL, n.iter = 1, output = c("list", "data.frame"), boot = FALSE, bootParams = NULL, parallel = c("no", "multicore", "snow"), ncpus = 1, cl = NULL, beep = NULL, ...) ``` ## Arguments - `func`: A user-defined function. The first argument to this function will be the iteration number. - `params`: A list or data frame of parameters to be passed to `func`. Each set of parameters will be passed to `func` in turn. - `n.iter`: Number of iterations (per set of params). - `output`: Specifies how `run_test` provides the ultimate output from `func`: can return a "list" or a "data.frame". Note that if "data.frame" is specified, the supplied function must return a vector, matrix, or data frame, so it can be coerced into the data frame format. The "list" option will accept any type of output. - `boot`: Whether or not to use bootstrapped data to pass along to `func`. Using this option instead of bootstrapping within `func` is preferable to take advantage of parallelization. - `bootParams`: If `boot=TRUE`, then use `bootParams` to pass along a named list of arguments to the `boot` function. The statistic and R parameters will be filled automatically, but at minimum you will need to pass along data. Information about parallel processing will also be passed along automatically. - `parallel`: The type of parallel operation to be used (if any). - `ncpus`: Integer: the number of processes to be used in parallel operation. - `cl`: An optional `parallel` or `snow` cluster for use if `parallel = 'snow'`. If not supplied, a cluster on the local machine is created for the duration of the iterations. - `beep`: Include a numeric value or character vector indicating the sound you wish to play once the tests are done running. If set to TRUE, a random sound will be played. Requires the 'beepr' package, and information about supported values is available in the documentation for that package. - `...`: Additional arguments to be passed to `func`. If you do not need to vary certain parameters in your model, you can pass them to `func` here. ## Returns Returns a list (by default) with one element per iteration. If `output` is specified as "data.frame", then `func` must return a (named) vector with the results you wish to capture. ## Examples ```r lm_test <- function(iter, N, b0, b1) { x <- rnorm(N, 0, 1) y <- rnorm(N, b0 + b1*x, sqrt(1 - b1^2)) data <- data.frame(y, x) model <- lm(y ~ x, data) # capture output from model summary est <- coef(summary(model))['x', 'Estimate'] se <- coef(summary(model))['x', 'Std. Error'] p <- coef(summary(model))['x', 'Pr(>|t|)'] return(c(xm=mean(x), xsd=sd(x), ym=mean(y), ysd=sd(y), est=est, se=se, p=p, sig=est > 0 & p <= .05)) } # test power for sample size N=200 and N=300, with 500 iterations for each power_sim <- run_test(lm_test, params=data.frame(N=c(200, 300)), n.iter=500, b0=0, b1=.15) ``` ## See Also `boot`

run_test function