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'pcts' is an R package for modelling periodically correlated and periodically integrated time series.

Installing pcts

Install the latest stable version of pcts from CRAN:

install.packages("pcts")

You can install the development version of pcts from Github:

library(remotes)
install_github("GeoBosh/pcts")

Overview

Periodic time series can be created with pcts(). Models are fitted with fitPM() and several other functions. To obtain periodic properties, such as sample periodic autocorrelations of periodic time series or theoretical periodic autocorrelations of periodic models, just call the respective functions (here autocorrelations() and partialAutocorrelations()) and they will compute the relevant property depending on the class of the argument, see the examples in the documentation.

A good place to start is the help topic ?pcts-package. Several datasets are available for examples and experiments. For example, ?dataFranses1996 contains the data from Franses (1996). The datasets are from classes "mts" or "ts" (the standard R classes for time series), so can be used without loading pcts, if desired.

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Version

Install

install.packages('pcts')

Monthly Downloads

299

Version

0.15.8

License

GPL (>= 2)

Issues

Pull Requests

Stars

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Repository

https://geobosh.github.io/pcts/ (doc) https://github.com/GeoBosh/pcts/ (devel)

Maintainer

Georgi Boshnakov

Last Published

March 17th, 2025

Functions in pcts (0.15.8)

ModelCycleSpec-class

Class ModelCycleSpec

PeriodicArModel-class

Class PeriodicArModel

PartialPeriodicAutocorrelations-class

Class PartialPeriodicAutocorrelations

PeriodicArmaFilter-class

Class "PeriodicArmaFilter"

PeriodicAutocovariances-class

Class PeriodicAutocovariances

PeriodicAutocorrelations-class

Class PeriodicAutocorrelations

PeriodicArmaModel-class

Class PeriodicArmaModel

PartialCycle-class

Class PartialCycle

PeriodicArModel-methods

Create objects from class PeriodicArModel

PeriodicArmaSpec-class

Class PeriodicArmaSpec

Convert between Pctime and datetime objects

PeriodicVector-class

Class PeriodicVector

PeriodicInterceptSpec-class

Class PeriodicInterceptSpec

PeriodicMTS_zooreg-class

Class "PeriodicMTS_zooreg"

PeriodicIntegratedArmaSpec-class

Class PeriodicIntegratedArmaSpec

PeriodicSPFilter-class

Class PeriodicSPFilter

PeriodicFilterModel-class

Class PeriodicFilterModel

PeriodicTS-class

Class "PeriodicTS"

PeriodicBJFilter-class

Class PeriodicBJFilter

PeriodicMaModel-class

Class PeriodicMaModel

PeriodicMTS-class

Class "PeriodicMTS"

PiPeriodicMaModel-class

Class PiPeriodicMaModel

PiPeriodicArmaModel-class

Class PiPeriodicArmaModel

PeriodicMTS_ts-class

Class "PeriodicMTS_ts"

VirtualPeriodicArmaModel-class

Class VirtualPeriodicArmaModel

PeriodicTS_ts-class

Class "PeriodicTS_ts"

SamplePeriodicAutocovariances-class

Class SamplePeriodicAutocovariances

PeriodicTimeSeries-class

Class PeriodicTimeSeries

SiPeriodicArmaModel-class

Class SiPeriodicArmaModel

SamplePeriodicAutocorrelations-class

Class SamplePeriodicAutocorrelations

PiPeriodicArModel-class

Class PiPeriodicArModel

SiPeriodicArModel-class

Class SiPeriodicArModel

VirtualPeriodicAutocovarianceModel-class

~~ Dummy title ~~

VirtualPeriodicAutocorrelations-class

~~ Dummy title ~~

Get names of seasons

VirtualPeriodicArModel-class

~~ Dummy title ~~

SiPeriodicMaModel-class

Class SiPeriodicMaModel

SLTypeMatrix-class

Class SLTypeMatrix

VirtualPeriodicMeanModel-class

~~ Dummy title ~~

VirtualPeriodicMaModel-class

~~ Dummy title ~~

PeriodicTS_zooreg-class

Class "PeriodicTS_zooreg"

SimpleCycle-class

Class SimpleCycle

VirtualPeriodicStationaryModel-class

~~ Dummy title ~~

autocovariances-methods

Compute autocovariances and periodic autocovariances

filterPoly-methods

~~ Dummy title ~~

Time of first or last non-NA value

Core data of periodic time series

as_datetime-methods

Methods for as_datetime in package pcts

VirtualPeriodicAutocovariances-class

~~ Dummy title ~~

VirtualPeriodicWhiteNoiseModel-class

~~ Dummy title ~~

filterPolyCoef-methods

~~ Dummy title ~~

VirtualPeriodicFilterModel-class

~~ Dummy title ~~

VirtualPeriodicModel-class

~~ Dummy title ~~

backwardPartialCoefficients-methods

Compute periodic backward partial coefficients

An example PAR autocorrelation function

as_date-methods

Replace methods for as_date in package pcts

autocorrelations-methods

Compute autocorrelations and periodic autocorrelations

filterCoef-methods

Get the coefficients of a periodic filter

Create environment for mc-fitting

backwardPartialVariances-methods

Compute periodic backward partial variances

Asymptotic covariance matrix of periodic mean

mcOptimCore-class

Class mcOptimCore

Methods for function maxLag() in package 'pcts'

nSeasons-methods

Number of seasons of a periodic object

partialAutocorrelations-methods

Compute periodic partial autocorrelations

VirtualPeriodicMonicFilter-class

~~ Dummy title ~~

Fit periodic time series models

partialCoefficients-methods

Compute periodic partial coefficients

Get the cycle of a periodic object

partialVariances-methods

Compute periodic partial variances

Number of observations in a time series

Give partial periodic autocorrelations or other partial prediction quantities for a pcAcvf object.

fit_trigPAR_optim

Fit a subset trigonometric PAR model

pc.filter.xarma

Filter time series with periodic arma filters

dataFranses1996

Example data from Franses (1996)

Fit PAR model using sample autocorrelations

Basic information about periodic ts objects

function to compute estimates of the h weights

Functions to compute various characteristics of a PCARMA model

Compute PAR autocovariance matrix

Compute asymptotic covariance matrix for PAR model

Functions for work with a simple list specification of pcarma models

partialAutocovariances-methods

Compute periodic partial autocovariances

Compute periodic autocorrelations from PAR coefficients

Periodic Levinson-Durbin algorithm

Generate a periodic autoregression model

Simulate periodically correlated ARMA series

pcts-deprecated

Deprecated Functions and classes in Package pcts

Virtual S4 class zooreg

pwn_McLeodLjungBox_test

McLeod-Ljung-Box test for periodic white noise

pcApply-methods

Apply a function to each season

permean2intercept

Convert between periodic centering and intercepts

Replace methods for date in package pcts

Test for periodicity

Compute the multi-companion form of a per model

Create objects from periodic time series classes

Simulate periodic white noise

four_stocks_since2016_01_01

Data for four stocks since 2016-01-01

Functions for some basic operations with seasons

Methods for function head() in package pcts

pcarma_acvf2model

Fit a PC-ARMA model to a periodic autocovariance function

Indexing of objects from classes in package pcts

Periodic methods for base R functions

Compute the sum of squares for a given PAR model

Applies a periodic ARMA filter to a time series

Compute normalising factors

Fit PAR models using least squares

Fit a periodically integrated autoregressive model

Variances of sample periodic autocorrelations

periodic_acf1_test

McLeod's test for periodic autocorrelation

Class zoo made S4

pcCycle-methods

Create or extract Cycle objects

Compute periodic mean

Convert PIAR coefficients to PAR coefficients

seqSeasons-methods

Methods for seqSeasons() in package pcts

Plot periodic time series

Periodic time series objects for examples

pd <- packageDescription("pcts") lb <- library(help="pcts", character.only=TRUE) lbinfo <- if(!is.null(lb$info[[2]])) lb$info[[2]] else "No_matches" anypat <- function(string, pat, ...){ any(sapply(pat, function(x) grepl(x, string, ...))) } lbsubset <- function(lbinfo, pat){ if(length(lbinfo) == 0) return("No entries") ind.start <- which(sapply(lbinfo, function(x) anypat(x, pat))) if(length(ind.start) == 0) return("No entries") ind.ws <- which(grepl("^[[:space:]]+", lbinfo)) res <- ind.start for(ind in ind.start){ while(any((ind+1) - ind.ws == 0)){ ind <- ind + 1 res <- c(res, ind) } } lbinfo[ sort(res) ] } lbpaste <- function(pat) paste("\\preformatted{", {wrk <- lbsubset(lbinfo,pat); wrk <- gsub("(^[^\\]?%)|(([^\\])%)", paste0("\\3", "\\\\", "%"), wrk); paste(if(length(wrk) > 0) wrk else "No entries", collapse="\n")}, "}", sep="") pd$Title

sigmaSq-methods

Methods for sigmaSq in package pcts

Methods for function tail() in package pcts

Methods for function`[[` in package 'pcts'

Index assignments for objects from classes in package pcts

Objects exported from other packages

Test for periodic integration

Create a random periodic autocovariance function

Functions for some basic operations with seasons

Methods for function$ in package 'pcts'

unitCycle-methods

Methods for unitCycle and unitSeason in package pcts

unitCycle<--methods

Methods for `unitCycle<-` and `unitSeason<-` in package pcts

FittedPeriodicArmaModel-class

Class FittedPeriodicArmaModel

BareCycle-class

Class BareCycle

BuiltinCycle-class

Class "BuiltinCycle" and its subclasses in package 'pcts'

BasicCycle-class

Class BasicCycle

Create objects from class Cyclic

Fraser River at Hope, mean monthly flow

Class "Cyclic"

FittedPeriodicArModel-class

Class FittedPeriodicArModel

LegacyPeriodicFilterModel-class

Class LegacyPeriodicFilterModel