Package: StableEstim 2.3

Georgi N. Boshnakov

StableEstim: Estimate the Four Parameters of Stable Laws using Different Methods

Estimate the four parameters of stable laws using maximum likelihood method, generalised method of moments with finite and continuum number of points, iterative Koutrouvelis regression and Kogon-McCulloch method. The asymptotic properties of the estimators (covariance matrix, confidence intervals) are also provided.

Authors:Tarak Kharrat [aut], Georgi N. Boshnakov [aut, cre]

StableEstim_2.3.tar.gz
StableEstim_2.3.tar.gz(r-4.5-noble)StableEstim_2.3.tar.gz(r-4.4-noble)
StableEstim_2.3.tgz(r-4.4-emscripten)StableEstim_2.3.tgz(r-4.3-emscripten)
StableEstim.pdf |StableEstim.html✨
StableEstim/json (API)
NEWS

# Install 'StableEstim' in R:
install.packages('StableEstim', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/geobosh/stableestim/issues

2.73 score 2 packages 18 scripts 693 downloads 30 exports 44 dependencies

Last updated 6 days agofrom:5b95322fed. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-linuxOKOct 25 2024

Exports:CgmmParametersEstimComplexCFComputeBest_tComputeBest_tauComputeDurationComputeFirstRootRealeCFComputeStatObjectFromFilesConcatFilesEstimEstim_Simulationexpect_almost_equalget.abMatget.StatFctsgetTime_GMMParametersEstimIGParametersEstiminitializeIntegrateRandomVectorsProductjacobianComplexCFKoutParametersEstimMcCullochParametersEstimMLParametersEstimPrintDurationPrintEstimatedRemainingTimeRegularisedSolrstablesampleComplexCFMomentsampleRealCFMomentshowTexSummary

Dependencies:briocallrclicrayondescdiffobjdigestevaluatefansifBasicsfsgluegssjsonlitelatticelifecyclemagrittrMASSMatrixnumDerivpillarpkgbuildpkgconfigpkgloadpraiseprocessxpsR6rbibutilsRdpackrematch2rlangrprojrootspatialstabledisttestthattibbletimeDatetimeSeriesutf8vctrswaldowithrxtable

Readme and manuals

Help Manual

Help pageTopics
Stable law estimation functionsStableEstim-package
Class '"Best_t"'+,Best_t,Best_t-method Best_t-class initialize,Best_t-method show,Best_t-method
Estimate parameters of stable laws using a Cgmm methodCgmmParametersEstim
Compute the characteristic function of stable lawsComplexCF
Monte Carlo simulation to investigate the optimal number of points to use in the moment conditionsComputeBest_t
Run Monte Carlo simulation to investigate the optimal tauComputeBest_tau
DurationComputeDuration
First root of the empirical characteristic functionComputeFirstRootRealeCF
Parse an output file to create a summary object ('list')ComputeStatObjectFromFiles
Concatenates output files.ConcatFiles
Estimate parameters of stable lawsEstim
Monte Carlo simulationEstim_Simulation
Class '"Estim"'Estim-class initialize,Estim-method show,Estim-method
Test approximate equalityexpect_almost_equal
Default set of parameters to pass to 'Estim_Simulation'get.abMat
Default functions used to produce the statistical summaryget.StatFcts
Read timegetTime_
Estimate parameters of stable laws using a GMM methodGMMParametersEstim
Estimate parameters of stable laws by Kogon and McCulloch methodsIGParametersEstim
Integral outer product of random vectorsIntegrateRandomVectorsProduct
Jacobian of the characteristic function of stable lawsjacobianComplexCF
Iterative Koutrouvelis regression methodKoutParametersEstim
Quantile-based methodMcCullochParametersEstim
Maximum likelihood (ML) methodMLParametersEstim
Print durationPrintDuration
Estimated remaining timePrintEstimatedRemainingTime
Regularised InverseRegularisedSol
Complex moment condition based on the characteristic functionsampleComplexCFMoment
Real moment condition based on the characteristic functionsampleRealCFMoment
Default functions used to produce the statistical summaryStatFcts
LaTeX summaryTexSummary