bssn (version 1.0)

momentsbssn: Moments for the Birnbaum-Saunders model based on Skew-Normal distribution

Description

Mean, variance, skewness and kurtosis for the Birnbaum-Saunders model based on Skew-Normal distribution defined in Filidor et. al (2011).

Usage

meanbssn(alpha=0.5,beta=1,lambda=1.5)
varbssn(alpha=0.5,beta=1,lambda=1.5)
skewbssn(alpha=0.5,beta=1,lambda=1.5)
kurtbssn(alpha=0.5,beta=1,lambda=1.5)

Arguments

alpha

shape parameter \(\alpha\).

beta

scale parameter \(\beta\).

lambda

skewness parameter \(\lambda\).

Value

meanbssn gives the mean, varbssn gives the variance, skewbssn gives the skewness, kurtbssn gives the kurtosis.

References

Vilca, Filidor; Santana, L. R.; Leiva, Victor; Balakrishnan, N. (2011). Estimation of extreme percentiles in Birnbaum Saunders distributions. Computational Statistics & Data Analysis (Print), 55, 1665-1678.

Santana, Lucia; Vilca, Filidor; Leiva, Victor (2011). Influence analysis in skew-Birnbaum Saunders regression models and applications. Journal of Applied Statistics, 38, 1633-1649.

See Also

bssn, EMbssn, momentsbssn, ozone, reliabilitybssn

Examples

# NOT RUN {
## Let's compute some moments for a Birnbaum-Saunders model based on Skew normal Distribution.
# The well known mean, variance, skewness and kurtosis
meanbssn(alpha=0.5,beta=1,lambda=1.5)
varbssn(alpha=0.5,beta=1,lambda=1.5)
skewbssn(alpha=0.5,beta=1,lambda=1.5)
kurtbssn(alpha=0.5,beta=1,lambda=1.5)
# }