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Simulate data from a multivariate normal distribution.

Source: R/DPI.R
sim_data.Rd

Simulate data from a multivariate normal distribution.

Usage

sim_data(n, k, cor = NULL, exact = TRUE, seed = NULL)

Arguments

n

Number of observations (cases).

k

Number of variables. Will be ignored if cor specifies a correlation matrix.

cor

A correlation value or correlation matrix of the variables. Defaults to NULL that generates completely random data regardless of their empirical correlations.

exact

Ensure the sample correlation matrix to be exact as specified in cor. This argument is passed on to empirical in mvrnorm(). Defaults to TRUE.

seed

Random seed for replicable results. Defaults to NULL.

Value

Return a data.frame of simulated data.

See also

cor_matrix()

sim_data_exp()

Examples

d1 = sim_data(n=100, k=5, seed=1)
cor_net(d1)
#> Displaying Correlation Network


d2 = sim_data(n=100, k=5, cor=0.2, seed=1)
cor_net(d2)
#> Displaying Correlation Network


cor.mat = cor_matrix(
  1.0, 0.7, 0.3,
  0.7, 1.0, 0.5,
  0.3, 0.5, 1.0
)
d3 = sim_data(n=100, cor=cor.mat, seed=1)
cor_net(d3)
#> Displaying Correlation Network