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Description

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>.

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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.

Metadata

Version

0.15.7

License

Unknown

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