snem {snem} | R Documentation |
EM algorithm in closed form.
snem(
x,
eps = 0.9,
iter.eps = 10^-6,
stop.rule = c("parameter", "log-likelihood")
)
x |
A data matrix. Each row is an observation vector. |
eps |
Weight parameter with |
iter.eps |
Convergence threshold. Default is 10^-6. |
stop.rule |
|
The parameter eps
is a tuning parameter which ensures that an initial covariance matrix is positive semi-definite.
Location parameter (mu
), covariance matrix (omega
), skewness parameter (delta
), and another expression of skewness parameter (lambda
).
Abe, T., Fujisawa, H., and Kawashima, T. (2019) EM algorithm using overparametrization for multivariate skew-normal distribution, in preparation.
library(sn)
data(ais, package="sn")
x <- ais[c("BMI")]
snem(x, stop.rule ="log-likelihood")