The characteristic function of a stable distribution
The characteristic function of a stable distribution
It computes the theoretical characteristic function of a stable distribution for two different parametrizations. It is used in the vignette to illustrate the estimation of the parameters using GMM.
charStable(theta, tau, pm =0)
Arguments
theta: Vector of parameters of the stable distribution. See details.
tau: A vector of numbers at which the function is evaluated.
pm: The type of parametization. It takes the values 0 or 1.
Returns
It returns a vector of complex numbers with the dimension equals to length(tau).
Details
The function returns the vector Ψ(θ,τ,pm) defined as E(eixτ, where τ is a vector of real numbers, i is the imaginary number, x is a stable random variable with parameters θ = (α,β,γ,δ) and pm is the type of parametrization. The vector of parameters are the characteristic exponent, the skewness, the scale and the location parameters, respectively. The restrictions on the parameters are: α∈(0,2], β∈[−1,1] and γ>0. For mode details see Nolan(2009).
References
Nolan J. P. (2020), Univariate Stable Distributions - Models for Heavy Tailed Data. Springer Series in Operations Research and Financial Engineering. URL https://edspace.american.edu/jpnolan/stable/.
Examples
# GMM is like GLS for linear models without endogeneity problemspm <-0theta <- c(1.5,.5,1,0)tau <- seq(-3,3, length.out =20)char_fct <- charStable(theta, tau, pm)