Learn R Programming
⚠️There's a newer version (1.7) of this package.Take me there.

perARMA (version 1.6)

Periodic Time Series Analysis

Description

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

Copy Link

Version

Install

install.packages('perARMA')

Monthly Downloads

295

Version

1.6

License

GPL (>= 2.0)

Maintainer

Wioletta Wojtowicz

Last Published

February 25th, 2016

Functions in perARMA (1.6)

arosa

Monthly stratospheric ozone, Arosa
volumes.sep

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

Periodic Time Series Analysis and Modeling
persigest

Periodic standard deviations
ab2phth

Fourier representation of real matrix
perYW

Yule-Walker estimators of PAR model
pgram

Plotting the periodogram of time series
predictperYW

Prediction for PAR model
loglikef

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

Plotting the squared coherence statistic of time series
R_w_ma

Covariance matrix for PARMA model (conditional)
peracf

Periodic ACF function
parmaresid

Computing residuals of PARMA series
parmaf

PARMA coefficients estimation
volumes

Volumes of energy, Nord Pool Spot Exchange
parma_ident

Identification of PC-T structure
perpacf

Periodic PACF function
Bcoeff, Bcoeffa

Fourier representation of covariance function
loglikec

Calculation of the logarithm of likelihood function
acfpacf

Plotting usual ACF and PACF
permest

Periodic Mean Estimation
makeparma

Simulation of PARMA sequence
parmafil

PARMA filtration