View source: R/NonparTrawlEstimation.R
asymptotic_variance | R Documentation |
This function computes the theoretical asymptotic variance appearing in the CLT of the trawl process for a given trawl function and fourth cumulant.
asymptotic_variance(t, c4, varlevyseed = 1, trawlfct, trawlfct_par)
t |
Time point at which the asymptotic variance is computed |
c4 |
The fourth cumulant of the Levy seed of the trawl process |
varlevyseed |
The variance of the Levy seed of the trawl process, the default is 1 |
trawlfct |
The trawl function for which the asymptotic variance will be computed (Exp, supIG or LM) |
trawlfct_par |
The parameter vector of the trawl function (Exp: lambda, supIG: delta, gamma, LM: alpha, H) |
As derived in Sauri and Veraart (2022), the asymptotic variance in the central limit theorem for the trawl function estimation is given by
σ_{a}^{2}(t)=c_{4}(L')a(t)+2\{ \int_{0}^{∞}a(s)^{2}ds+ \int_{0}^{t}a(t-s)a(t+s)ds-\int_{t}^{∞}a(s-t)a(t+s)ds\},
for t>0. The integrals in the above formula are approximated numerically.
The function returns σ_{a}^{2}(t).
#Compute the asymptotic variance at time t for an exponential trawl with #parameter 2; here we assume that the fourth cumulant equals 1. av<-asymptotic_variance(t=1, c4=1, varlevyseed=1, trawlfct="Exp", trawlfct_par=2) #Print the av av$v #Print the four components of the asymptotic variance separately av$v1 av$v2 av$v3 av$v4 #Note that v=v1+v2+v3+v4 av$v av$v1+av$v2+av$v3+av$v4
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.