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StableEstim overview

StableEstim-package
Stable law estimation functions

Estimation of stable laws

Estim()
Estimate parameters of stable laws
CgmmParametersEstim()
Estimate parameters of stable laws using a Cgmm method
GMMParametersEstim()
Estimate parameters of stable laws using a GMM method
IGParametersEstim()
Estimate parameters of stable laws by Kogon and McCulloch methods
KoutParametersEstim()
Iterative Koutrouvelis regression method
MLParametersEstim()
Maximum likelihood (ML) method
McCullochParametersEstim()
Quantile-based method
Estim_Simulation()
Monte Carlo simulation
get.abMat()
Default set of parameters to pass to Estim_Simulation

CF of stable distributions

ComplexCF()
Compute the characteristic function of stable laws
ComputeFirstRootRealeCF()
First root of the empirical characteristic function
jacobianComplexCF()
Jacobian of the characteristic function of stable laws
sampleComplexCFMoment()
Complex moment condition based on the characteristic function
sampleRealCFMoment()
Real moment condition based on the characteristic function

Regularisation and parameter tuning

RegularisedSol()
Regularised Inverse
IntegrateRandomVectorsProduct()
Integral outer product of random vectors
ComputeBest_t()
Monte Carlo simulation to investigate the optimal number of points to use in the moment conditions
ComputeBest_tau()
Run Monte Carlo simulation to investigate the optimal \(\tau\)

Classes

Summaries

get.StatFcts()
Default functions used to produce the statistical summary
StatFcts
Default functions used to produce the statistical summary
TexSummary()
LaTeX summary

Other

expect_almost_equal()
Test approximate equality
ConcatFiles()
Concatenates output files.
ComputeStatObjectFromFiles()
Parse an output file to create a summary object (list)
ComputeDuration()
Duration
getTime_()
Read time
PrintDuration()
Print duration
PrintEstimatedRemainingTime()
Estimated remaining time