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rcorrelationmontecarlo

Monte Carlo Simulation to generate two related variables in R

I am looking for a way to generate two related variables from a normal distribution with Monte Carlo simulation using R. Specifically, I want to define different correlations between these two variables (i.e., r = .30, .60, .90). Thanks a lot!

Solution

  • You can use rnorm_multi() from the faux package:

    library("faux")

x <- rnorm_multi(n = 1000, vars = 2, r = 0.9)
cor.test(x$X1, x$X2)
#> 
#>  Pearson's product-moment correlation
#> 
#> data:  x$X1 and x$X2
#> t = 65.537, df = 998, p-value < 2.2e-16
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  0.8884275 0.9118777
#> sample estimates:
#>       cor 
#> 0.9008074