Description Usage Arguments Value References Examples
Density, cumulative distribution function, quantile function and random sample generation from the quantile-based asymmetric exponential power distribution (AEPD) studied in Gijbels et al. (2019b). An alternative form of the density AEPD is also studied in Komunjer (2007).
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y, q |
These are each a vector of quantiles. |
mu |
This is the location parameter μ. |
phi |
This is the scale parameter φ. |
alpha |
This is the index parameter α. |
p |
This is the shape parameter, which must be positive. |
beta |
This is a vector of probabilities. |
n |
This is the number of observations, which must be a positive integer that has length 1. |
dAEPD
provides the density, pAEPD
provides the cumulative distribution function, qAEPD
provides the quantile function, and rAEPD
generates a random sample from the quantile-based asymmetric exponential power distribution.
Gijbels, I., Karim, R. and Verhasselt, A. (2019b). Quantile estimation in a generalized asymmetric distributional setting. To appear in Springer Proceedings in Mathematics & Statistics, Proceedings of ‘SMSA 2019’, the 14th Workshop on Stochastic Models, Statistics and their Application, Dresden, Germany, in March 6–8, 2019. Editors: Ansgar Steland, Ewaryst Rafajlowicz, Ostap Okhrin.
Komunjer, I., (2007). Asymmetric power distribution: theory and applications to risk measurement. Journal of Applied Econometrics, 22(5), 891-921.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # Quantile-based asymmetric exponential power distribution
# Density
rnum<-rnorm(100)
dAEPD(y=rnum,mu=0,phi=1,alpha=.5,p=2)
# Distribution function
pAEPD(q=rnum,mu=0,phi=1,alpha=.5,p=2)
# Quantile function
beta<-c(0.25,0.5,0.75)
qAEPD(beta=beta,mu=0,phi=1,alpha=.5,p=2)
# random sample generation
rAEPD(n=100,mu=0,phi=1,alpha=.5,p=2)
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