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
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