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ambit

Simulation and estimation tools for various types of ambit processes, including trawl processes and weighted trawl processes.

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Version

Install

install.packages('ambit')

Monthly Downloads

364

Version

0.1.2

License

GPL-3

Maintainer

Almut D. Veraart

Last Published

August 19th, 2022

Functions in ambit (0.1.2)

c4est

Estimating the fourth cumulant of the trawl process
rq

Computing the scaled realised quarticity
nonpar_trawlest

Nonparametric estimation of the trawl function
test_asymnorm

Computing the infeasible test statistic from the trawl function estimation CLT
test_asymnorm_est

Computing the feasible statistic of the trawl function CLT
asymptotic_variance_est

Estimating the asymptotic variance in the trawl function CLT
trawl_Exp

Evaluates the exponential trawl function
test_asymnorm_est_dev

Computing the feasible statistic of the trawl function CLT
trawl_LM

Evaluates the long memory trawl function
my_mae

my_mse
sim_weighted_trawl

Simulation of a weighted trawl process
trawl_deriv_mod

Estimating the derivative of the trawl function
trawl_deriv

Estimating the derivative of the trawl function using the empirical derivative
trawl_supIG

Evaluates the supIG trawl function
sim_weighted_trawl_gen

Simulation of a weighted trawl process with generic trawl function
my_mse

my_mse
my_results

my_results
asymptotic_variance

Computing the true asymptotic variance in the CLT of the trawl estimation
acf_supIG

Autocorrelation function of the supIG trawl function
acf_LM

Autocorrelation function of the long memory trawl function
LebA_est

Nonparametric estimation of the trawl set Leb(A)
LebA_slice_est

Nonparametric estimation of the trawl (sub-) sets Leb(A), Leb(A intersection A_h), Leb(A setdifference A_h)
LebA_slice_ratio_est_acfbased

Nonparametric estimation of the ratios Leb(A intersection A_h)/Leb(A), Leb(A setdifference A_h)/Leb(A)
acf_Exp

Autocorrelation function of the exponential trawl function
AddSlices_Rcpp

Add slices and return vector of the sums of slices
AddWeightedSlices_Rcpp

Add slices and return vector of the weighted sums of slices