armafit {timsac} | R Documentation |
Fit an ARMA model with specified order by using DAVIDON's algorithm.
armafit(y, model.order, tmp.file=NULL)
y |
a univariate time series. |
model.order |
a numerical vector of the form c(ar, ma) which gives the order to be fitted successively. |
tmp.file |
a character string naming a file written intermediate results of model fitting. If NULL (default) output no file. |
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 algorithm. Pure autoregression is not allowed.
arcoef |
maximum likelihood estimates of AR coefficients. |
macoef |
maximum likelihood estimates of MA coefficients. |
arstd |
standard deviation (AR). |
mastd |
standard deviation (MA). |
v |
innovation variance. |
aic |
AIC. |
grad |
final gradient. |
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.
# "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=c(-0.5)), n=1000) z <- armafit(y, model.order=c(2,1)) z$arcoef z$macoef