dbinvgaussgeo: The bivariate inverse-Gaussian geometric distribution (BIGG)

In camponsah/BivMixDist: Fit bivariate continous and discrete distributions as well as provide EM algorithm for discrete Pareto

Description

Density function for bivariate inverse-Gaussian geometric distribution with parameters μ >0, φ > 0 and p in (0,1).

Usage

dbinvgaussgeo(data, mu, phi, p, log.p = FALSE)

Arguments

data	bivariate vector (X,N) observations from BIGG model.
mu	mean paramter which must be numeric greater than 0.
phi	shape paramter which must be numeric greater than 0.
p	numeric parameter between 0 and 1.
log.p	logical; if TRUE, probabilities p are given as log(p).

Details

dbinvgaussgeo is the density function for BIGG model.

Value

vector of densities.

References

Barreto-Souza, W. and Silva R. B., (2019). A bivariate infinitely divisible law for modeling the magnitude and duration of monotone periods of log-returns . Statistica Neerlandica, 73:211-233. https://doi.org/10.1111/stan.12166

Examples

data.df<-rbinvgaussgeo(20,mu=1.5, phi=2, p=0.6)
den<-rbinvgaussgeo(data.df,mu=1.5, phi=2, p=0.6)
den

camponsah/BivMixDist documentation built on Nov. 15, 2021, 3:11 a.m.