Description Usage Arguments Value Functions Author(s) References See Also Examples
Computing the mean, variance, skewness and kurtosis for the split-normal distribution.
1 2 3 4 5 6 7 | splitn_kurtosis(lmd)
splitn_mean(mu, sigma, lmd)
splitn_skewness(sigma, lmd)
splitn_var(sigma, lmd)
|
lmd |
vector of skewness parameters (>0). If is 1, reduce to normal distribution. |
mu |
vector of location parameter. (The mode of the density) |
sigma |
vector of standard deviations. |
splitn_mean
gives the mean. splitn_var
gives the
variance. splitn_skewness
gives the skewness.
splitn_kurtosis
gives the kurtosis. (splitn_mean
,
splitn_var
,splitn_skeness
and splitn_kurtosis
are all
vectors.
splitn_kurtosis
: Kurtosis for the split-normal distribution.
splitn_skewness
: Skewness for the split-normal distribution.
splitn_var
: Variance for the split-normal distribution.
Feng Li, Jiayue Zeng
Villani, M., & Larsson, R. (2006) The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis. Sveriges Riksbank Working Paper Series, No. 175.
psplitn()
dsplitn()
qsplitn()
and
rsplitn()
for the split-normal distribution.
1 2 3 4 5 6 7 8 | mu <- c(0,1,2)
sigma <- c(0.5,1,2)
lmd <- c(1,2,3)
mean0 <- splitn_mean(mu, sigma, lmd)
var0 <- splitn_var(sigma, lmd)
skewness0 <- splitn_skewness(sigma, lmd)
kurtosis0 <- splitn_kurtosis(lmd)
|
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