pcbrom / bgev

We propose a new model Bimodal Generalized Extreme value.

bgev

We propose a new model Bimodal Generalized Extreme value.

Installation

You can install the released version of bgev from CRAN with:

or using devtools

devtools::install_git('https://github.com/pcbrom/bgev')

Load package

library(bgev)

Density Function

dbgev(x = 2, csi = 1, mu = 1, sigma = 1, delta = 1)
curve(dbgev(x, csi = 1, mu = 1, sigma = 1, delta = 1), xlim = c(-1, 10))
integrate(dbgev, csi = 1, mu = 1, sigma = 1, delta = 1, lower = -Inf, upper = Inf)

Distribution Function

pbgev(2, csi = 1, mu = 2, sigma = 1, delta = 2)
pbgev(2, csi = 1, mu = 2, sigma = 1, delta = 2, lower.tail = FALSE)
curve(pbgev(x, csi = 1, mu = 2, sigma = 1, delta = 2), xlim = c(-1, 10))

Quantile Function

curve(pbgev(x, csi = 1, mu = 2, sigma = 1, delta = 2), xlim = c(-5, 5))
(value <- qbgev(p = .25, csi = 1, mu = 2, sigma = 1, delta = 2, initial = 1, final = 2))
pbgev(value, csi = 1, mu = 2, sigma = 1, delta = 2)
curve(pbgev(x, csi = .1, mu = 2, sigma = 1, delta = 2), xlim = c(-5, 5))
(value <- qbgev(p = .5, csi = .1, mu = 2, sigma = 1, delta = 2, initial = 0, final = 3))
pbgev(value, csi = .1, mu = 2, sigma = 1, delta = 2)

Pseudo-Random Numbers Generator

Theoretical E(X) and empirical first moment

Theoretical E(X²) and empirical second moment

Maximum Likelihood Estimation

GEV Density Function (additional function implemented)

dgev(x = 2, csi = 0, mu = 1, sigma = 1)
curve(dgev(x, csi = 0, mu = 1, sigma = 1), xlim = c(-5, 10), ylim= c(0, .4))
integrate(dgev, csi = 0, mu = 1, sigma = 1, lower = -5, upper = 0)

GEV Distribution Function (additional function implemented)

pgev(0, csi = 0, mu = 1, sigma = 1)
integrate(dgev, csi = 0, mu = 1, sigma = 1, lower = -Inf, upper = 0)
pgev(0, csi = 0, mu = 1, sigma = 1, lower.tail = FALSE)
curve(pgev(x, csi = 0, mu = 1, sigma = 1), xlim = c(-5, 10))

Issues

Please, send to: https://github.com/pcbrom/bgev/issues

To cite package ‘bgev’ in publications use

citation("bgev")