ArmaStatistics | R Documentation |
A collection and description of functions to compute statistics of
a true ARMA time series process.
The functions are:
armaRoots | Roots of the characteristic ARMA polynomial, |
armaTrueacf | True autocorrelation function of an ARMA process. |
armaRoots(coefficients, n.plot = 400, digits = 4, ...) armaTrueacf(model, lag.max = 20, type = c("correlation", "partial", "both"), doplot = TRUE)
coefficients |
[armaRoots] - |
digits |
[armaRoots] - |
doplot |
[armaRoots] - |
lag.max |
[armaTrueacf] - |
model |
[armaTrueacf] - |
n |
[armaSim] - |
n.plot |
[armaRoots] - |
type |
[armaTrueacf] - |
... |
additional arguments to be passed. |
armaRoots
returns a three column data frame with the real, the imaginary part
and the radius of the roots. The number of rows corresponds
to the coefficients.
armaTrueacf
returns a two column data frame with the lag and the correlation
function.
M. Plummer and B.D. Ripley for ar
functions and code,
B.D. Ripley for arima
and ARMAacf
functions and code,
C. Fraley and F. Leisch for fracdiff
functions and code, and
Diethelm Wuertz for the Rmetrics R-port.
Brockwell, P.J. and Davis, R.A. (1996); Introduction to Time Series and Forecasting, Second Edition, Springer, New York.
Durbin, J. and Koopman, S.J. (2001); Time Series Analysis by State Space Methods, Oxford University Press.
Gardner, G, Harvey, A.C., Phillips, G.D.A. (1980); Algorithm AS154. An algorithm for exact maximum likelihood estimation of autoregressive-moving average models by means of Kalman filtering, Applied Statistics, 29, 311–322.
Hannan E.J. and Rissanen J. (1982); Recursive Estimation of Mixed Autoregressive-Moving Average Order. Biometrika 69, 81–94.
Harvey, A.C. (1993); Time Series Models, 2nd Edition, Harvester Wheatsheaf, Sections 3.3 and 4.4.
Jones, R.H. (1980); Maximum likelihood fitting of ARMA models to time series with missing observations, Technometrics, 20, 389–395.
Percival, D.P. and Walden, A.T. (1998); Spectral Analysis for Physical Applications. Cambridge University Press.
Whittle, P. (1963); On the fitting of multivariate autoregressions and the approximate canonical factorization of a spectral matrix. Biometrika 40, 129–134.
Haslett J. and Raftery A.E. (1989); Space-time Modelling with Long-memory Dependence: Assessing Ireland's Wind Power Resource (with Discussion), Applied Statistics 38, 1–50.
## armaRoots - # Calculate and plot the roots of an ARMA process: par(mfrow = c(2, 2), cex = 0.7) coefficients = c(-0.5, 0.9, -0.1, -0.5) armaRoots(coefficients) ## armaTrueacf - model = list(ar = c(0.3, +0.3), ma = 0.1) armaTrueacf(model) model = list(ar = c(0.3, -0.3), ma = 0.1) armaTrueacf(model)
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