Make normally distributed vectors with specified relationships. See vignette("rnorm_multi", package = "faux") for details.
Usage
rnorm_multi(
n = 100,
vars = NULL,
mu = 0,
sd = 1,
r = 0,
varnames = NULL,
empirical = FALSE,
as.matrix = FALSE,
seed = NULL
)Arguments
- n
the number of samples required
- vars
the number of variables to return
- mu
a vector giving the means of the variables (numeric vector of length 1 or vars)
- sd
the standard deviations of the variables (numeric vector of length 1 or vars)
- r
the correlations among the variables (can be a single number, vars\*vars matrix, vars\*vars vector, or a vars\*(vars-1)/2 vector)
- varnames
optional names for the variables (string vector of length vars) defaults if r is a matrix with column names
- empirical
logical. If true, mu, sd and r specify the empirical not population mean, sd and covariance
- as.matrix
logical. If true, returns a matrix
- seed
DEPRECATED use set.seed() instead before running this function
Examples
# 4 10-item vectors each correlated r = .5
rnorm_multi(10, 4, r = 0.5)
#> X1 X2 X3 X4
#> 1 1.4328938 0.71046741 -0.3545094 0.3296056
#> 2 0.5499955 -0.04515263 0.5200758 0.3126072
#> 3 1.2332014 0.84059575 1.4636452 1.2133793
#> 4 1.5940614 0.33277182 1.1490795 1.5716986
#> 5 -0.5075202 -1.20328029 -1.6145986 -1.5344455
#> 6 -0.7985165 -1.96248137 -1.7310021 -2.4968725
#> 7 -2.6613942 -1.51496840 -0.1958377 -1.1080823
#> 8 1.5503841 0.22264712 -0.4416368 0.7515796
#> 9 -0.1089382 -1.19677372 0.3412923 0.9013702
#> 10 -0.4104137 0.06785565 -0.1272144 -0.8141842
# set r with the upper right triangle
b <- rnorm_multi(100, 3, c(0, .5, 1), 1,
r = c(0.2, -0.5, 0.5),
varnames=c("A", "B", "C"))
cor(b)
#> A B C
#> A 1.0000000 0.2612873 -0.4747722
#> B 0.2612873 1.0000000 0.5104176
#> C -0.4747722 0.5104176 1.0000000
# set r with a correlation matrix and column names from mu names
c <- rnorm_multi(
n = 100,
mu = c(A = 0, B = 0.5, C = 1),
r = c( 1, 0.2, -0.5,
0.2, 1, 0.5,
-0.5, 0.5, 1)
)
cor(c)
#> A B C
#> A 1.0000000 0.3562369 -0.4429172
#> B 0.3562369 1.0000000 0.4324168
#> C -0.4429172 0.4324168 1.0000000