Simulate covariates using a copula

Couples several marginal distributions using a copula to generate correlated multivariate covariates.

Usage

simulate_X_copula(n, p, cp, margins, paramMargins)

Arguments

n

Positive integer. Number of units to simulate.

p

Positive integer. Number of covariates. Must equal the dimension of `cp`.

cp

A copula object (from the `copula` package).

margins

Character vector of length `p`. Names of marginal distributions (e.g. `"norm"`, `"binom"`).

paramMargins

List of length `p`. Each element is a named list of parameters for the corresponding marginal distribution.

Value

A data frame with `n` rows and `p` columns named `x1`, ..., `xp`.

Examples

normal <- copula::normalCopula(param = c(0.8), dim = 4, dispstr = "ar1")
X <- simulate_X_copula(1000, 4, normal,
  margins = c("norm", "t", "norm", "binom"),
  paramMargins = list(
    list(mean = 2, sd = 3),
    list(df = 2),
    list(mean = 0, sd = 1),
    list(size = 10, prob = 0.5)
  )
)
cor(X, method = "spearman")
#>           x1        x2        x3        x4
#> x1 1.0000000 0.7843630 0.6290593 0.4916759
#> x2 0.7843630 1.0000000 0.7785835 0.6156791
#> x3 0.6290593 0.7785835 1.0000000 0.7689832
#> x4 0.4916759 0.6156791 0.7689832 1.0000000