pcts0.15.7 package

Periodically Correlated and Periodically Integrated Time Series

PeriodicBJFilter-class

Class PeriodicBJFilter

PeriodicFilterModel-class

Class PeriodicFilterModel

PeriodicIntegratedArmaSpec-class

Class PeriodicIntegratedArmaSpec

PeriodicInterceptSpec-class

Class PeriodicInterceptSpec

PeriodicMaModel-class

Class PeriodicMaModel

PeriodicMTS-class

Class "PeriodicMTS"

PeriodicMTS_ts-class

Class "PeriodicMTS_ts"

PeriodicMTS_zooreg-class

Class "PeriodicMTS_zooreg"

PeriodicSPFilter-class

Class PeriodicSPFilter

PeriodicTimeSeries-class

Class PeriodicTimeSeries

PeriodicTS-class

Class "PeriodicTS"

PeriodicTS_ts-class

Class "PeriodicTS_ts"

PeriodicTS_zooreg-class

Class "PeriodicTS_zooreg"

PeriodicVector-class

Class PeriodicVector

permean2intercept

Convert between periodic centering and intercepts

permodelmf

Compute the multi-companion form of a per model

pi1ar2par

Convert PIAR coefficients to PAR coefficients

PiPeriodicArmaModel-class

Class PiPeriodicArmaModel

PiPeriodicArModel-class

Class PiPeriodicArModel

PiPeriodicMaModel-class

Class PiPeriodicMaModel

SamplePeriodicAutocorrelations-class

Class SamplePeriodicAutocorrelations

SamplePeriodicAutocovariances-class

Class SamplePeriodicAutocovariances

seqSeasons-methods

Methods for seqSeasons() in package pcts

sigmaSq-methods

Methods for sigmaSq in package pcts

sim_parAcvf

Create a random periodic autocovariance function

sim_parCoef

Generate a periodic autoregression model

sim_pc

Simulate periodically correlated ARMA series

sim_pwn

Simulate periodic white noise

pc.hat.h

function to compute estimates of the h weights

pc.modelunvec

Functions for work with a simple list specification of pcarma models

pc.test.LjungBox

McLeod-Ljung-Box test for periodic white noise

pc.test.periodicity

McLeod's test for periodic autocorrelation

pc.wn.var.acrf

Variances of sample periodic autocorrelations

pc_sdfactor

Compute normalising factors

allSeasons

Get names of seasons

as_date-methods

Replace methods for as_date in package pcts

as_datetime-methods

Methods for as_datetime in package pcts

autocorrelations-methods

Compute autocorrelations and periodic autocorrelations

autocovariances-methods

Compute autocovariances and periodic autocovariances

availStart

Time of first or last non-NA value

backwardPartialCoefficients-methods

Compute periodic backward partial coefficients

backwardPartialVariances-methods

Compute periodic backward partial variances

BareCycle-class

Class BareCycle

BasicCycle-class

Class BasicCycle

BuiltinCycle-class

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

Cyclic-class

Class "Cyclic"

Cyclic

Create objects from class Cyclic

date_ass-methods

Replace methods for date in package pcts

filterCoef-methods

Get the coefficients of a periodic filter

filterPoly-methods

~~ Dummy title ~~

filterPolyCoef-methods

~~ Dummy title ~~

fit_trigPAR_optim

Fit a subset trigonometric PAR model

fitPM

Fit periodic time series models

FittedPeriodicArmaModel-class

Class FittedPeriodicArmaModel

FittedPeriodicArModel-class

Class FittedPeriodicArModel

head-methods

Methods for function head() in package pcts

LegacyPeriodicFilterModel-class

Class LegacyPeriodicFilterModel

maxLag-methods

Methods for function maxLag() in package 'pcts'

mC.ss

Create environment for mc-fitting

mcOptimCore-class

Class mcOptimCore

meanvarcheck

Asymptotic covariance matrix of periodic mean

modelCycle

Get the cycle of a periodic object

ModelCycleSpec-class

Class ModelCycleSpec

nCycles

Basic information about periodic ts objects

nSeasons-methods

Number of seasons of a periodic object

nTicks-methods

Number of observations in a time series

num2pcpar

Fit PAR model using sample autocorrelations

parcovmatlist

Compute asymptotic covariance matrix for PAR model

partialAutocorrelations-methods

Compute periodic partial autocorrelations

partialAutocovariances-methods

Compute periodic partial autocovariances

partialCoefficients-methods

Compute periodic partial coefficients

PartialCycle-class

Class PartialCycle

PartialPeriodicAutocorrelations-class

Class PartialPeriodicAutocorrelations

partialVariances-methods

Compute periodic partial variances

pc.acf2model

Fit a PC-ARMA model to a periodic autocovariance function

pc.filter

Applies a periodic ARMA filter to a time series

pc.filter.xarma

Filter time series with periodic arma filters

pcacfMat

Compute PAR autocovariance matrix

pcalg1

Periodic Levinson-Durbin algorithm

pcalg1util

Give partial periodic autocorrelations or other partial prediction qua...

pcApply-methods

Apply a function to each season

pcAr.ss

Compute the sum of squares for a given PAR model

pcAR2acf

Compute periodic autocorrelations from PAR coefficients

pcarma_solve

Functions to compute various characteristics of a PCARMA model

pcCycle-methods

Create or extract Cycle objects

pclsdf

Fit PAR models using least squares

pclspiar

Fit a periodically integrated autoregressive model

pcMean-methods

Compute periodic mean

pcPlot

Plot periodic time series

pcTest-methods

Test for periodicity

Pctime

Convert between Pctime and datetime objects

pcts-deprecated

Deprecated Functions and classes in Package pcts

pcts-methods

Create objects from periodic time series classes

pcts-package

pd <- packageDescription("pcts") lb <- library(help="pcts", characte...

pcts_exdata

Periodic time series objects for examples

pcts_reexports

Objects exported from other packages

pdSafeParOrder

Functions for some basic operations with seasons

PeriodicArmaFilter-class

Class "PeriodicArmaFilter"

PeriodicArmaModel-class

Class PeriodicArmaModel

PeriodicArmaSpec-class

Class PeriodicArmaSpec

PeriodicArModel-class

Class PeriodicArModel

PeriodicArModel-methods

Create objects from class PeriodicArModel

PeriodicAutocorrelations-class

Class PeriodicAutocorrelations

PeriodicAutocovariances-class

Class PeriodicAutocovariances

SimpleCycle-class

Class SimpleCycle

SiPeriodicArmaModel-class

Class SiPeriodicArmaModel

SiPeriodicArModel-class

Class SiPeriodicArModel

SiPeriodicMaModel-class

Class SiPeriodicMaModel

sl_utils

Functions for some basic operations with seasons

SLTypeMatrix-class

Class SLTypeMatrix

SubsetPM-class

Class SubsetPM

tail-methods

Methods for function tail() in package pcts

test_piar

Test for periodic integration

unitCycle-methods

Methods for unitCycle and unitSeason in package pcts

unitCycle_ass-methods

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

Vec

Core data of periodic time series

VirtualPeriodicArmaModel-class

Class VirtualPeriodicArmaModel

VirtualPeriodicArModel-class

~~ Dummy title ~~

VirtualPeriodicAutocorrelations-class

~~ Dummy title ~~

VirtualPeriodicAutocovarianceModel-class

~~ Dummy title ~~

VirtualPeriodicAutocovariances-class

~~ Dummy title ~~

VirtualPeriodicFilterModel-class

~~ Dummy title ~~

VirtualPeriodicMaModel-class

~~ Dummy title ~~

VirtualPeriodicMeanModel-class

~~ Dummy title ~~

VirtualPeriodicModel-class

~~ Dummy title ~~

VirtualPeriodicMonicFilter-class

~~ Dummy title ~~

VirtualPeriodicStationaryModel-class

~~ Dummy title ~~

VirtualPeriodicWhiteNoiseModel-class

~~ Dummy title ~~

window

Periodic methods for base R functions

zoo-class

Class zoo made S4

zooreg-class

Virtual S4 class zooreg

zzbracket-methods

Indexing of objects from classes in package pcts

zzbracket_ass

Index assignments for objects from classes in package pcts

zzbracket_bracket-methods

Methods for function[[ in package 'pcts'

zzdollar-methods

Methods for function$ in package 'pcts'

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>.

  • Maintainer: Georgi N. Boshnakov
  • License: GPL (>= 2)
  • Last published: 2023-11-25