hw | R Documentation |
Performs the high-dimensional version of the BHEP test for multivariate normality as proposed by Henze and Wagner (1997). When the covariance matrix is singular (e.g., when p > n) a Moore-Penrose pseudoinverse is used.
hw(
data,
use_population = TRUE,
tol = 1e-25,
bootstrap = FALSE,
B = 1000,
cores = 1
)
data |
A numeric matrix or data frame with observations in rows and variables in columns. |
use_population |
Logical; if |
tol |
Numeric tolerance passed to |
bootstrap |
Logical; if |
B |
Integer; number of bootstrap replicates used when
|
cores |
Integer; number of cores for parallel computation when
|
A data frame with one row containing the following columns:
Test
("Henze-Wagner"), Statistic
and p.value
.
## Not run:
data <- iris[1:50, 1:4]
hw_result <- hw(data)
hw_result
## End(Not run)
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