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Make a normal vector correlated to existing vectors

Source: R/rnorm_pre.R
rnorm_pre.Rd

rnorm_pre Produces a random normally distributed vector with the specified correlation to one or more existing vectors

Usage

rnorm_pre(x, mu = 0, sd = 1, r = 0, empirical = FALSE, threshold = 1e-12)

Arguments

x

the existing vector or data table of all vectors

mu

desired mean of returned vector

sd

desired SD of returned vector

r

desired correlation(s) between existing and returned vectors

empirical

logical. If true, mu, sd and r specify the empirical not population mean, sd and covariance

threshold

for checking correlation matrix

Value

vector

Examples

v1 <- rnorm(10)
v2 <- rnorm_pre(v1, 0, 1, 0.5)
cor(v1, v2)
#> [1] 0.9586105

x <- rnorm_multi(50, 2, .5)
x$y <- rnorm_pre(x, r = c(0.5, 0.25))
cor(x)
#>            X1         X2         y
#> X1  1.0000000 -0.1679038 0.5438173
#> X2 -0.1679038  1.0000000 0.2765696
#> y   0.5438173  0.2765696 1.0000000