Package: ACDm 1.1.0

Markus Belfrage

ACDm: Tools for Autoregressive Conditional Duration Models

Provides tools for autoregressive conditional duration (ACD, Engle and Russell, 1998) models. Functions to create trade, price, or volume durations from transaction data, perform diurnal adjustments, fit various ACD models, and test them.

Authors:Markus Belfrage [aut, cre]

ACDm_1.1.0.tar.gz
ACDm_1.1.0.tar.gz(r-4.7-arm64)ACDm_1.1.0.tar.gz(r-4.7-x86_64)ACDm_1.1.0.tar.gz(r-4.6-arm64)ACDm_1.1.0.tar.gz(r-4.6-x86_64)
ACDm_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ACDm/json (API)

# Install 'ACDm' in R:
install.packages('ACDm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

2.23 score 3 stars 1 packages 19 scripts 430 downloads 45 exports 46 dependencies

Last updated from:d9ecb027a1. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK176
linux-devel-x86_64OK182
source / vignettesOK213
linux-release-arm64OK179
linux-release-x86_64OK183
wasm-releaseOK553

Exports:acdFitacf_acdburrExpectationcomputeDurationsdburrdgenfdgengammadiurnalAdjdmixinvgaussdmixqwedmixqwwdqweibullgenfHazardgengammaHazardmixinvgaussHazardmixqweHazardmixqwwHazardpburrpgenfpgengammaplotDescTransplotHazardplotHistAcdplotLLplotRollMeanAcdplotScatterAcdpmixinvgausspmixqwepmixqwwpqweibullqburrqgengammaqqplotAcdqqweibullqweibullExpectationqweibullHazardrburrresiDensityAcdrgengammarqweibullsim_ACDstandardizeResitestRmACDtestSTACDtestTVACD

Dependencies:backportsbroomclicodetoolscpp11digestdplyrfarverfuturefuture.applygenericsggplot2globalsgluegtableisobandlabelinglatticelifecyclelistenvmagrittrnumDerivparallellypillarpkgconfigplyrpurrrR6RColorBrewerRcppRcppArmadillorlangRsolnpS7scalesstringistringrtibbletidyrtidyselecttruncnormutf8vctrsviridisLitewithrzoo

Readme and manuals

Help Manual

Help pageTopics
ACD ModellingACDm-package ACDm
ACD (Autoregressive Conditional Duration) Model FittingacdFit
Methods for class acdFitacdFit-methods coef.acdFit predict.acdFit print.acdFit residuals.acdFit
Autocorrelation function plots for ACD modelsacf_acd
The Burr DistributionBurrDist burrExpectation dburr pburr qburr rburr
Durations computationcomputeDurations
Time Series Data SetsadjDurData DataFiles defaultSplineObj durData transData
The generalized F distributiondgenf genfHazard pgenf
Discreet mix of the Q-Weibull and the exponential distributionsDiscreetly mixed Q-Weibull and exponential dmixqwe mixqweHazard pmixqwe
Discreet mix of the q-Weibull and the ordinary Weibull distributionsDiscreetly mixed Q-Weibull and ordinary Weibull dmixqww mixqwwHazard pmixqww
Dirunal adjustment for durationsdiurnalAdj
Finite mixture of inverse Gaussian Distributiondmixinvgauss Finite mixture of inverse Gaussian Distributions mixinvgaussHazard pmixinvgauss
The generelized Gamma distributiondgengamma GeneralizedGammaDist gengammaHazard pgengamma qgengamma rgengamma
Transactions plotsplotDescTrans
Hazard function plotplotHazard
Mean duration plotplotHistAcd
Plots the response surface of the log likelihood of a fitted model.plotLL
Plots rolling means of durationsplotRollMeanAcd
Scatter plot for ACD modelsplotScatterAcd
Quantile-Quantile plot of the residualsqqplotAcd
The q-Weibull distributiondqweibull pqweibull qqweibull qWeibullDist qweibullExpectation qweibullHazard rqweibull
Residual Density HistogramresiDensityAcd
ACD simulationsim_ACD
Residual standardizationstandardizeResi
LM test of no Remaining ACD (Meitz and Terasvirta, 2006)testRmACD
LM test against Smooth Transition ACD models (Meitz and Terasvirta, 2006)testSTACD
LM test against Time-Varying ACD models (Meitz and Terasvirta, 2006)testTVACD