univ: Generate Univariate Data
In jeksterslabds/jeksterslabRdata: Jekster's Lab Data Generation Utilities

Description Usage Arguments Details Value Author(s) Examples

View source: R/univ.R

Generates an n \times 1 univariate data vector or a list of n \times 1 univariate data vectors of length R. The default data generating function is the normal distribution

X \sim \mathcal{N} ≤ft( μ, σ^2 \right) . %(\#eq:dist-X-norm)

univ(
  n,
  rFUN = rnorm,
  ...,
  R = NULL,
  par = FALSE,
  ncores = NULL,
  mc = TRUE,
  lb = FALSE,
  cl_eval = FALSE,
  cl_export = FALSE,
  cl_expr,
  cl_vars,
  rbind = NULL
)

`n`	Integer. Sample size.
`rFUN`	Function. Data generating function to generate univariate data.
`...`	Arguments to pass to `rFUN`.
`R`	Integer. Number of Monte Carlo replications. If `R` is not provided, the function produces a single random data set. If `R` is an integer greater than 1, (e.g., `R = 10`), the function produces multiple random data sets stored in each element of a list of length `R`. `par` and all succeeding arguments are only relevant when `R > 1`.
`par`	Logical. If `TRUE`, use multiple cores. If `FALSE`, use `lapply()`.
`ncores`	Integer. Number of cores to use if `par = TRUE`. If unspecified, defaults to `detectCores() - 1`.
`mc`	Logical. If `TRUE`, use `parallel::mclapply()`. If `FALSE`, use `parallel::parLapply()` or `parallel::parLapplyLB()`. Ignored if `par = FALSE`.
`lb`	Logical. If `TRUE` use `parallel::parLapplyLB()`. If `FALSE`, use `parallel::parLapply()`. Ignored if `par = FALSE` and `mc = TRUE`.
`cl_eval`	Logical. Execute `parallel::clusterEvalQ()` using `cl_expr`. Ignored if `mc = TRUE`.
`cl_export`	Logical. Execute `parallel::clusterExport()` using `cl_vars`. Ignored if `mc = TRUE`.
`cl_expr`	Expression. Expression passed to `parallel::clusterEvalQ()` Ignored if `mc = TRUE`.
`cl_vars`	Character vector. Names of objects to pass to `parallel::clusterExport()` Ignored if `mc = TRUE`.
`rbind`	NULL or logical. If `rbind = NULL`, returns the list produced. If `TRUE`, uses `rbind()` to bind the rows of the list produced. If `FALSE`, uses `cbind()` to bind the columns of the list produced. Test that each element of the output list has the appropriate dimensions for binding before using this option.

The univariate distribution and parameters used in the data generating process can be specified using rFUN and ....

Options for explicit parallelism are provided when R > 1 especially when R is large. See par and suceeding arguments.

If R = NULL or R = 1, returns an n \times 1 univariate data vector generated using rFUN and parameters passed to .... If R is an integer greater than 1, (e.g., R = 10) returns a list of length R of n \times 1 univariate data vector generated using rFUN and parameters passed to ....

Ivan Jacob Agaloos Pesigan

x <- univ(n = 100, rFUN = rnorm, mean = 100, sd = sqrt(225))
str(x)
xstar <- univ(n = 100, rFUN = rnorm, mean = 100, sd = sqrt(225), R = 100)
str(xstar, list.len = 6)