bgev (version 0.2)

bgev-package: tools:::Rd_package_title("bgev")

Description

tools:::Rd_package_description("bgev")

Usage

dbgev(y, mu = 1, sigma = 1, xi = 0.3, delta = 2)
pbgev(y, mu = 1, sigma = 1, xi = 0.3, delta = 2)
qbgev(p, mu = 1, sigma = 1, xi = 0.3, delta = 2)
rbgev(n, mu = 1, sigma = 1, xi = 0.3, delta = 2)

Value

dbgev gives the density, pbgev gives the distribution function, qbgev gives the quantile function, and rbgev generates random bimodal GEV observations.

Arguments

y

a unidimensional vector containing the points to compute the density (dbgev) or the probability (pbgev) froma bimodal GEV distribution with parameters mu, sigma, xi and delta.

p

a unidimensional vector containing the probabilities used to compute the quantiles

n

an integer describing the number of observations to generate random bimodal GEV observations

mu

location parameter

sigma

shape parameter

xi

shape parameter

delta

bimodality parameter

Author

tools:::Rd_package_author("bgev")

Maintainer: tools:::Rd_package_maintainer("bgev")

Details

Density, distribution function, quantile function and random generation of bimodal GEV distribution with location parameter. In addition, maximum likelihood estimation based on real data is also provided.

References

Otiniano, Cira EG, et al. (2023). A bimodal model for extremes data. Environmental and Ecological Statistics, 1-28. http://dx.doi.org/10.1007/s10651-023-00566-7

Examples

# generate 100 values distributed according to a bimodal GEV
x = rbgev(50, mu = 0.2, sigma = 1, xi = 0.5, delta = 0.2) 
# estimate the bimodal GEV parameters using the generated data
bgev.mle(x)