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perARMA (version 1.4)

Package for Periodic Time Series Analysis

Description

The package includes procedures for identification, model fitting and estimation for time series with periodic structure. Additionally procedures for simulation of periodic processes and real data sets are included.

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Version

Install

install.packages('perARMA')

Monthly Downloads

189

Version

1.4

License

GPL (>= 2.0)

Maintainer

Wioletta Wojtowicz

Last Published

February 26th, 2013

Functions in perARMA (1.4)

permest

Periodic Mean Estimation
parma_ident

Identification of PC-T structure
predictperYW

Prediction for PAR model
loglikef

Calculation of the logarithm of likelihood function (using Fourier representation)
R_w_ma

Covariance matrix for PARMA model (conditional)
peracf

Periodic ACF function
perYW

Yule-Walker estimators of PAR model
volumes

Volumes of energy, Nord Pool Spot Exchange
makeparma

Simulation of PARMA sequence
volumes.sep

Volumes of energy, Nord Pool Spot Exchange, from 1st and 2nd September 2010.
persigest

Periodic standard deviations
perARMA-package

Periodic Time Series Analysis and Modeling
parmaf

PARMA coefficients estimation
parmafil

PARMA filtration
perpacf

Periodic PACF function
acfpacf

Plotting usual ACF and PACF
parmaresid

Computing residuals of PARMA series
ab2phth

Fourier representation of real matrix
loglikec

Calculation of the logarithm of likelihood function
pgram

Plotting the periodogram of time series
Bcoeff, Bcoeffa

Fourier representation of covariance function
scoh

Plotting the squared coherence statistic of time series
arosa

Monthly stratospheric ozone, Arosa