autoarmafit {timsac} | R Documentation |
Automatic ARMA Model Fitting
Description
Provide an automatic ARMA model fitting procedure. Models with various orders are fitted and the best choice is determined with the aid of the statistics AIC.
Usage
autoarmafit(y, max.order = NULL)
Arguments
y |
a univariate time series. |
max.order |
upper limit of AR order and MA order. Default is
|
Details
The maximum likelihood estimates of the coefficients of a scalar ARMA model
y(t) - a(1)y(t-1) -...- a(p)y(t-p) = u(t) - b(1)u(t-1) -...- b(q)u(t-q)
of a time series y(t)
are obtained by using DAVIDON's variance algorithm.
Where p
is AR order, q
is MA order and u(t)
is a zero mean
white noise. Pure autoregression is not allowed.
Value
best.model |
the best choice of ARMA coefficients. |
model |
a list with components |
References
H.Akaike, E.Arahata and T.Ozaki (1975) Computer Science Monograph, No.5, Timsac74, A Time Series Analysis and Control Program Package (1). The Institute of Statistical Mathematics.
Examples
# "arima.sim" is a function in "stats".
# Note that the sign of MA coefficient is opposite from that in "timsac".
y <- arima.sim(list(order=c(2,0,1),ar=c(0.64,-0.8),ma=-0.5), n = 1000)
autoarmafit(y)