Package: pcts 0.15.2.9000
Georgi N. Boshnakov
pcts: Periodically Correlated and Periodically Integrated Time Series
Classes and methods for modelling and simulation of periodically correlated (PC) and periodically integrated time series. Compute theoretical periodic autocovariances and related properties of PC autoregressive moving average models. Some original methods including Boshnakov & Iqelan (2009) <doi:10.1111/j.1467-9892.2009.00617.x>, Boshnakov (1996) <doi:10.1111/j.1467-9892.1996.tb00281.x>.
Authors:
pcts_0.15.2.9000.tar.gz
pcts_0.15.2.9000.zip(r-4.5)pcts_0.15.2.9000.zip(r-4.4)pcts_0.15.2.9000.zip(r-4.3)
pcts_0.15.2.9000.tgz(r-4.4-any)pcts_0.15.2.9000.tgz(r-4.3-any)
pcts_0.15.2.9000.tar.gz(r-4.5-noble)pcts_0.15.2.9000.tar.gz(r-4.4-noble)
pcts_0.15.2.9000.tgz(r-4.4-emscripten)pcts_0.15.2.9000.tgz(r-4.3-emscripten)
pcts.pdf |pcts.html✨
pcts/json (API)
NEWS
| # Install 'pcts' in R: |
| install.packages('pcts', repos = c('https://geobosh.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/geobosh/pcts/issues
Datasets:
- Fraser2017 - Fraser River at Hope, mean monthly flow
- dataFranses1996 - Example data from Franses
- ex1f - An example PAR autocorrelation function
- four_stocks_since2016_01_01 - Data for four stocks since 2016-01-01
par-modelsperiodicperiodic-modelspiar-modelsseasonaltime-seriestime-series-models
Last updated 10 months agofrom:5ef809a876. Checks:OK: 1 ERROR: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 28 2024 |
| R-4.5-win | ERROR | Aug 28 2024 |
| R-4.5-linux | ERROR | Aug 28 2024 |
| R-4.4-win | ERROR | Aug 28 2024 |
| R-4.4-mac | ERROR | Aug 28 2024 |
| R-4.3-win | ERROR | Aug 28 2024 |
| R-4.3-mac | ERROR | Aug 28 2024 |
Exports:[.Pctime[[.Pctimealg1alg1utilallSeasonsallSeasons<-as_dateas_datetimeas_Pctimeas.Dateas.Date.Cyclicas.Date.PeriodicTimeSeriesautocorrelationsautocovariancesavailEndavailStartbackwardPartialCoefficientsbackwardPartialVariancesBuiltinCyclecoefCyclicdatedate.Cyclicdate<-filterCoeffilterOrderfilterPolyfilterPolyCoeffit_trigPAR_optimfitPMfittedheadintercept2permeanisStationaryModelmaxLagmC.ssmeancovmatmeanvarcheckmodelCentermodelCoefmodelCyclemodelCycle<-modelInterceptmodelOrdermodelPolymodelPolyCoefna.trimnCyclesnSeasonsnTicksnum2pcparnUnitRootsnVariablesparcovmatlistpartialAutocorrelationspartialAutocovariancespartialCoefficientspartialVariancespc_sdfactorpc.acf.parModelpc.filterpc.filter.xarmapc.hat.hpc.sdfactorpcacf_pwn_varpcacfMatpcApplypcAr.sspcAR2acfpcarma_acvf_lazypcarma_acvf_systempcarma_acvf2modelpcarma_hpcarma_h_lazypcarma_param_systempcarma_preparepcarma_tovecpcarma_unvecpcArraypcCyclepclsdfpclspiarpcMatrixpcMeanpcTestPctimepctspcts_exdatapctsArraypdSafeParOrderperiodic_acf1_testPeriodicArModelPeriodicVectorpermean2interceptpermodelmfpi1ar2parplotpwn_McLeodLjungBox_testresidualsseqSeasonssigmaSqsim_parAcvfsim_parCoefsim_pcsim_pwnslMatrixtailtest_piartoSeasontoSeasonPairtsMatrixtsVectsVectorttmatToslPairsttToslunitCycleunitCycle<-unitSeasonunitSeason<-vcovVecxx.ss
Dependencies:BBcpp11FormulagbutilsgenericslaggedlatticeltsalubridateMASSMatrixmcompanionnumDerivPolynomFquadprogrbibutilsRcppRcppArmadilloRdpacksarimatimechangextszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Periodically Correlated and Periodically Integrated Time Series | pcts-package |
| Indexing of objects from classes in package pcts | [,BasicCycle,ANY,missing,ANY-method [,BasicCycle,missing,missing,ANY-method [,PeriodicMTS,ANY,ANY,ANY-method [,PeriodicMTS,ANY,missing,ANY-method [,PeriodicMTS,AnyDateTime,ANY,ANY-method [,PeriodicMTS,AnyDateTime,missing,ANY-method [,PeriodicMTS,missing,missing,ANY-method [,PeriodicTS,AnyDateTime,missing,ANY-method [,PeriodicTS,missing,missing,ANY-method [,PeriodicVector,ANY,ANY,ANY-method [,PeriodicVector,ANY,missing,ANY-method [,PeriodicVector,missing,ANY,ANY-method [,PeriodicVector,missing,missing,ANY-method [,VirtualPeriodicAutocovarianceModel,missing,missing,ANY-method [,VirtualPeriodicAutocovarianceModel,missing,numeric,ANY-method [,VirtualPeriodicAutocovarianceModel,numeric,missing,ANY-method [,VirtualPeriodicAutocovarianceModel,numeric,numeric,ANY-method [-methods |
| Methods for function'`[[`' in package 'pcts' | [[,PeriodicAutocovarianceModel,numeric-method [[,PeriodicMTS,ANY,ANY-method [[,PeriodicMTS,ANY-method [[,VirtualPeriodicAutocovarianceModel,numeric,ANY-method [[-methods |
| Index assignments for objects from classes in package pcts | [<-,ANY,ANY,ANY,ANY-method [<-,BasicCycle,ANY,missing,ANY-method [<-,BasicCycle,missing,missing,ANY-method [<-,pc.armaPQ,ANY,ANY,ANY-method [<-,PeriodicAutocovarianceModel,ANY,ANY,ANY-method [<-,PeriodicVector,ANY,ANY,ANY-method [<-,PeriodicVector,missing,ANY,ANY-method [<-,slMatrix,ANY,ANY,ANY-method [<--methods |
| Methods for function'$' in package 'pcts' | $,PeriodicMTS-method $-methods |
| Get names of seasons | allSeasons allSeasons,BasicCycle,ANY-method allSeasons,Cyclic,ANY-method allSeasons,DayWeekCycle,logical-method allSeasons,DayWeekCycle,missing-method allSeasons,Every30MinutesCycle,logical-method allSeasons,Every30MinutesCycle,missing-method allSeasons,MonthYearCycle,logical-method allSeasons,MonthYearCycle,missing-method allSeasons,OpenCloseCycle,logical-method allSeasons,OpenCloseCycle,missing-method allSeasons,QuarterYearCycle,logical-method allSeasons,QuarterYearCycle,missing-method allSeasons,SimpleCycle,ANY-method allSeasons,VirtualPeriodicModel,ANY-method allSeasons-methods allSeasons<- allSeasons<-,Cyclic-method allSeasons<-,SimpleCycle-method seqSeasons unitCycle unitCycle<- unitSeason unitSeason<- |
| Replace methods for as_date in package pcts | as_date,ANY-method as_date,character-method as_date,Cyclic-method as_date,numeric-method as_date,PeriodicTimeSeries-method as_date,POSIXt-method as_date-methods |
| Methods for as_datetime in package pcts | as_datetime,PeriodicTimeSeries-method as_datetime-methods |
| Compute autocorrelations and periodic autocorrelations | autocorrelations autocorrelations,numeric,ANY,missing-method autocorrelations,PeriodicAutocovariances,ANY,missing-method autocorrelations,PeriodicTimeSeries,ANY,missing-method autocorrelations,SamplePeriodicAutocovariances,ANY,missing-method autocorrelations,VirtualPeriodicAutocovarianceModel,ANY,missing-method autocorrelations,VirtualPeriodicAutocovariances,ANY,missing-method autocorrelations-methods |
| Compute autocovariances and periodic autocovariances | autocovariances autocovariances,matrix,ANY-method autocovariances,matrix-method autocovariances,numeric,ANY-method autocovariances,numeric-method autocovariances,PeriodicArmaModel,ANY-method autocovariances,PeriodicArmaModel-method autocovariances,PeriodicArModel,ANY-method autocovariances,PeriodicArModel-method autocovariances,PeriodicTS,ANY-method autocovariances,VirtualPeriodicAutocovariances,ANY-method autocovariances-methods |
| Time of first or last non-NA value | availEnd availStart |
| Compute periodic backward partial coefficients | backwardPartialCoefficients,VirtualPeriodicAutocovariances-method backwardPartialCoefficients-methods |
| Compute periodic backward partial variances | backwardPartialVariances,VirtualPeriodicAutocovariances-method backwardPartialVariances-methods |
| Class BareCycle | BareCycle-class |
| Class BasicCycle | BasicCycle-class |
| Class '"BuiltinCycle"' and its subclasses in package 'pcts' | allSeasons,BuiltinCycle-method BuiltinCycle-class DayWeekCycle-class Every30MinutesCycle-class initialize,BuiltinCycle-method MonthYearCycle-class OpenCloseCycle-class QuarterYearCycle-class unitCycle,BuiltinCycle-method unitSeason,BuiltinCycle-method |
| Create objects from class Cyclic | as.Date.Cyclic as.Date.PeriodicTimeSeries Cyclic date.Cyclic date<- |
| Class '"Cyclic"' | Cyclic-class |
| Example data from Franses (1996) | dataFranses1996 |
| Replace methods for date in package pcts | date<-,BasicCycle-method date<-,Cyclic-method date<--methods |
| An example PAR autocorrelation function | ex1f |
| Get the coefficients of a periodic filter | filterCoef,PeriodicBJFilter,character-method filterCoef,PeriodicSPFilter,character-method filterCoef-methods |
| Fit a subset trigonometric PAR model | fit_trigPAR_optim |
| Fit periodic time series models | fitPM fitPM,ANY,ANY-method fitPM,mcSpec,ANY-method fitPM,numeric,ANY-method fitPM,PeriodicArModel,ANY-method fitPM,PeriodicArModel,PeriodicMTS-method fitPM,PeriodicArModel,PeriodicTS-method fitPM,PiPeriodicArModel,ANY-method fitPM,SiPeriodicArModel,ANY-method fitPM-methods |
| Class FittedPeriodicArmaModel | as_pcarma_list,FittedPeriodicArmaModel-method FittedPeriodicArmaModel-class show,FittedPeriodicArmaModel-method |
| Class FittedPeriodicArModel | FittedPeriodicArModel-class |
| Data for four stocks since 2016-01-01 | four_stocks_since2016_01_01 |
| Fraser River at Hope, mean monthly flow | Fraser2017 |
| Methods for function maxLag() in package 'pcts' | maxLag,PeriodicArmaFilter-method maxLag-methods |
| Create environment for mc-fitting | mC.ss xx.ss |
| Asymptotic covariance matrix of periodic mean | meancovmat meanvarcheck |
| Get the cycle of a periodic object | modelCycle modelCycle,ANY-method modelCycle,ModelCycleSpec-method modelCycle-methods modelCycle<- modelCycle<-,ANY-method modelCycle<-,ModelCycleSpec-method modelCycle<--methods |
| Class ModelCycleSpec | ModelCycleSpec-class |
| Basic information about periodic ts objects | nCycles nSeasons nTicks nVariables |
| Number of seasons of a periodic object | nSeasons,BareCycle-method nSeasons,Cyclic-method nSeasons,DayWeekCycle-method nSeasons,Every30MinutesCycle-method nSeasons,MonthYearCycle-method nSeasons,OpenCloseCycle-method nSeasons,PartialCycle-method nSeasons,PeriodicFilterModel-method nSeasons,PeriodicIntegratedArmaSpec-method nSeasons,PeriodicInterceptSpec-method nSeasons,PeriodicMonicFilterSpec-method nSeasons,QuarterYearCycle-method nSeasons,SarimaFilter-method nSeasons,VirtualArmaFilter-method nSeasons,VirtualPeriodicArmaFilter-method nSeasons,VirtualPeriodicModel-method nSeasons-methods |
| Fit PAR model using sample autocorrelations | num2pcpar |
| Compute asymptotic covariance matrix for PAR model | parcovmatlist |
| Compute periodic partial autocorrelations | partialAutocorrelations partialAutocorrelations,PeriodicAutocovariances,ANY,missing-method partialAutocorrelations,VirtualPeriodicAutocovariances,ANY,ANY-method partialAutocorrelations-methods |
| Compute periodic partial autocovariances | partialAutocovariances,VirtualPeriodicAutocovariances-method partialAutocovariances-methods |
| Compute periodic partial coefficients | partialCoefficients partialCoefficients,PeriodicArModel-method partialCoefficients,VirtualPeriodicAutocovariances-method partialCoefficients-methods |
| Class PartialCycle | allSeasons,PartialCycle,logical-method allSeasons,PartialCycle,missing-method PartialCycle-class |
| Class PartialPeriodicAutocorrelations | PartialPeriodicAutocorrelations-class |
| Compute periodic partial variances | partialVariances partialVariances,VirtualPeriodicAutocovariances-method partialVariances-methods |
| Compute normalising factors | pc.sdfactor pc_sdfactor |
| Applies a periodic ARMA filter to a time series | pc.armafilter pc.filter |
| Filter time series with periodic arma filters | pc.filter.xarma |
| function to compute estimates of the h weights | pc.hat.h |
| Variances of sample periodic autocorrelations | pcacf_pwn_var |
| Compute PAR autocovariance matrix | pc.acf.parModel pcacfMat |
| Periodic Levinson-Durbin algorithm | alg1 |
| Give partial periodic autocorrelations or other partial prediction quantities for a pcAcvf object. | alg1util |
| Apply a function to each season | pcApply pcApply,matrix-method pcApply,numeric-method pcApply,PeriodicMTS-method pcApply,PeriodicTS-method pcApply-methods |
| Compute the sum of squares for a given PAR model | pcAr.ss |
| Compute periodic autocorrelations from PAR coefficients | pcAR2acf |
| Fit a PC-ARMA model to a periodic autocovariance function | pcarma_acvf2model |
| Functions to compute various characteristics of a PCARMA model | pcarma_acvf_lazy pcarma_acvf_system pcarma_h pcarma_h_lazy pcarma_param_system |
| Functions for work with a simple list specification of pcarma models | pcarma_prepare pcarma_tovec pcarma_unvec |
| Create or extract Cycle objects | BuiltinCycle pcCycle pcCycle,BasicCycle,character-method pcCycle,BasicCycle,missing-method pcCycle,character,ANY-method pcCycle,character,character-method pcCycle,character,missing-method pcCycle,Cyclic,ANY-method pcCycle,numeric,character-method pcCycle,numeric,missing-method pcCycle,PeriodicTimeSeries,character-method pcCycle,PeriodicTimeSeries,missing-method pcCycle,ts,character-method pcCycle,ts,missing-method pcCycle-methods |
| Fit PAR models using least squares | pclsdf |
| Fit a periodically integrated autoregressive model | pclspiar |
| Compute periodic mean | pcMean pcMean,matrix-method pcMean,numeric-method pcMean,PeriodicMTS-method pcMean,PeriodicTS-method pcMean,VirtualPeriodicArmaModel-method pcMean-methods |
| Plot periodic time series | boxplot.PeriodicTimeSeries monthplot.PeriodicTimeSeries pcPlot |
| Test for periodicity | pcTest pcTest,ANY,ANY-method pcTest,ANY,character-method pcTest,numeric,character-method pcTest,PeriodicTimeSeries,character-method pcTest,slMatrix,character-method pcTest-methods |
| Convert between Pctime and datetime objects | as_Pctime as_Pctime.Cyclic as_Pctime.PeriodicTimeSeries Pctime [.Date [.Pctime [.ts [<-.POSIXlt [[.Date [[.Pctime |
| Create objects from periodic time series classes | pcts pcts,ANY-method pcts,data.frame,ANY-method pcts,matrix,BasicCycle-method pcts,matrix,missing-method pcts,matrix,numeric-method pcts,mts,missing-method pcts,mts,numeric-method pcts,numeric,BasicCycle-method pcts,numeric,missing-method pcts,numeric,numeric-method pcts,ts,missing-method pcts,ts,numeric-method pcts,xtsORzoo,missing-method pcts-methods |
| Periodic time series objects for examples | pcts_exdata |
| Deprecated Functions and classes in Package 'pcts' | allSeasons,FiveDayWeekCycle,logical-method allSeasons,FiveDayWeekCycle,missing-method FiveDayWeekCycle-class mCpar nSeasons,FiveDayWeekCycle-method pcts-deprecated ptildeorders sim_arAcf unitCycle,FiveDayWeekCycle-method unitSeason,FiveDayWeekCycle-method |
| Functions for some basic operations with seasons | pdSafeParOrder |
| McLeod's test for periodic autocorrelation | periodic_acf1_test |
| Class '"PeriodicArmaFilter"' | PeriodicArFilter-class PeriodicArmaFilter-class PeriodicMaFilter-class |
| Class PeriodicArmaModel | PeriodicArmaModel-class |
| Class PeriodicArmaSpec | innovationVariances,PeriodicArmaSpec-method PeriodicArmaSpec-class |
| Class PeriodicArModel | PeriodicArModel-class |
| Create objects from class PeriodicArModel | PeriodicArModel PeriodicArModel,matrix-method PeriodicArModel,numeric-method PeriodicArModel,PeriodicArmaModel-method PeriodicArModel,PeriodicMonicFilterSpec-method PeriodicArModel,VirtualPeriodicArmaModel-method PeriodicArModel-methods |
| Class PeriodicAutocorrelations | PeriodicAutocorrelations-class plot,PeriodicAutocorrelations,missing-method |
| Class PeriodicAutocovariances | PeriodicAutocovariances-class |
| Class PeriodicBJFilter | PeriodicBJFilter-class PeriodicMonicFilterSpec-class |
| Class PeriodicFilterModel | PeriodicFilterModel-class |
| Class PeriodicIntegratedArmaSpec | PeriodicIntegratedArmaSpec-class |
| Class PeriodicInterceptSpec | PeriodicInterceptSpec-class |
| Class PeriodicMaModel | PeriodicMaModel-class |
| Class '"PeriodicMTS_ts"' | PeriodicMTS_ts-class |
| Class '"PeriodicMTS_zooreg"' | PeriodicMTS_zooreg-class |
| Class '"PeriodicMTS"' | PeriodicMTS-class plot,PeriodicMTS,missing-method |
| Class PeriodicSPFilter | PeriodicSPFilter-class |
| Class PeriodicTimeSeries | PeriodicTimeSeries-class |
| Class '"PeriodicTS_ts"' | PeriodicTS_ts-class |
| Class '"PeriodicTS_zooreg"' | PeriodicTS_zooreg-class |
| Class '"PeriodicTS"' | coerce,mts,PeriodicTS-method coerce,PeriodicTS,ts-method coerce,ts,PeriodicTS-method PeriodicTS-class plot,PeriodicTS,missing-method show,PeriodicTS-method summary,PeriodicTS-method |
| Class PeriodicVector | PeriodicVector PeriodicVector-class |
| Convert between periodic centering and intercepts | intercept2permean permean2intercept |
| Compute the multi-companion form of a per model | permodelmf |
| Convert PIAR coefficients to PAR coefficients | pi1ar2par piar2par |
| Class PiPeriodicArmaModel | PiPeriodicArmaModel-class |
| Class PiPeriodicArModel | PiPeriodicArModel-class |
| Class PiPeriodicMaModel | PiPeriodicMaModel-class |
| McLeod-Ljung-Box test for periodic white noise | pwn_McLeodLjungBox_test |
| Class SamplePeriodicAutocorrelations | SamplePeriodicAutocorrelations-class |
| Class SamplePeriodicAutocovariances | SamplePeriodicAutocovariances-class |
| Methods for seqSeasons() in package pcts | seqSeasons,BasicCycle-method seqSeasons,Cyclic-method seqSeasons,VirtualPeriodicModel-method seqSeasons-methods |
| Methods for 'sigmaSq' in package pcts | sigmaSq,PeriodicIntegratedArmaSpec-method sigmaSq,PeriodicInterceptSpec-method sigmaSq-methods |
| Create a random periodic autocovariance function | sim_parAcvf |
| Generate a periodic autoregression model | sim_parCoef |
| Simulate periodically correlated ARMA series | sim_pc |
| Simulate periodic white noise | sim_pwn |
| Class SimpleCycle | SimpleCycle-class |
| Class SiPeriodicArmaModel | SiPeriodicArmaModel-class |
| Class SiPeriodicArModel | SiPeriodicArModel-class |
| Class SiPeriodicMaModel | SiPeriodicMaModel-class |
| Functions for some basic operations with seasons | toSeason toSeasonPair ttmatToslPairs ttTosl |
| Class SubsetPM | coef,SubsetPM-method fitted,SubsetPM-method residuals,SubsetPM-method show,SubsetPM-method SubsetPM-class vcov,SubsetPM-method |
| Test for periodic integration | test_piar |
| Methods for 'unitCycle' and 'unitSeason' in package pcts | unitCycle,ANY-method unitCycle,Cyclic-method unitCycle,DayWeekCycle-method unitCycle,Every30MinutesCycle-method unitCycle,MonthYearCycle-method unitCycle,OpenCloseCycle-method unitCycle,PartialCycle-method unitCycle,QuarterYearCycle-method unitCycle,SimpleCycle-method unitCycle,VirtualPeriodicModel-method unitCycle-methods unitSeason,ANY-method unitSeason,Cyclic-method unitSeason,DayWeekCycle-method unitSeason,Every30MinutesCycle-method unitSeason,MonthYearCycle-method unitSeason,OpenCloseCycle-method unitSeason,PartialCycle-method unitSeason,QuarterYearCycle-method unitSeason,SimpleCycle-method unitSeason,VirtualPeriodicModel-method unitSeason-methods |
| Methods for '`unitCycle<-`' and '`unitSeason<-`' in package pcts | unitCycle<-,Cyclic-method unitCycle<-,SimpleCycle-method unitCycle<--methods unitSeason<-,Cyclic-method unitSeason<-,SimpleCycle-method unitSeason<--methods |
| Core data of periodic time series | pcArray pcMatrix pctsArray tsMatrix tsVec tsVector Vec |
| Periodic methods for base R functions | cycle.PeriodicTimeSeries deltat.PeriodicTimeSeries end.Cyclic frequency.PeriodicTimeSeries na.trim na.trim.PeriodicMTS na.trim.PeriodicTS start.Cyclic time.PeriodicTimeSeries window window.PeriodicMTS window.PeriodicTS |
| Class zoo made S4 | zoo-class |
| Virtual S4 class zooreg | zooreg-class |