Realization of the process (a univariate or multivariate time series
object).
logdata
Logarithm of absdata (a univariate or multivariate time
series object).
logstoch
Log-stochastic component (a univariate or multivariate time series
object).
logresid
Random component (a univariate time series object).
Note
decompose.mar1s and fit.mar1s compute the random
component in different ways: decompose.mar1s uses filter
while fit.mar1s saves the residuals returned by arima.
The results may be different in:
the first value:
decompose.mar1s uses specified
init.absdata while arima always assumes zero initial
values for the fitted process;
non-finite values:
decompose.mar1s handles non-finite
values more accurately.
See Also
compose.ar1 for the AR(1) with external regressors
processes, fit.mar1s for fitting MAR(1)S process to
data, sim.mar1s for MAR(1)S process simulation and
prediction.