Fitting an ARIMA model with Exogeneous Variables
Description
This function is identical to the arimax function which builds on and extends the capability of the arima function in R stats by allowing the incorporation of transfer functions, and innovative and additive outliers. For backward compatitibility, the function is also named arima. Note in the computation of AIC, the number of parameters excludes the noise variance. This function is heavily based on the arima function of the stats core of R.
Usage
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Arguments
x 
time series response 
order 
regular ARIMA order 
seasonal 
seasonal ARIMA order 
xreg 
a dataframe containing covariates 
include.mean 
if true, an intercept term is incorporated in the model; applicable only to stationary models. 
transform.pars 
if true, the AR parameters are transformed to ensure stationarity 
fixed 
a vector indicating which coefficients are fixed or free 
init 
initial values 
method 
estimation method 
n.cond 
number of initial values to be conditioned on in a conditional analysis 
optim.control 
control parameters for the optimization procedure 
kappa 
prior variance; used in dealing with initial values 

All of the above parameters have the same usage as those in the arima function. Please check the help manual of the arima function. Below are new options. 
io 
a list of time points at which the model may have an innovative outlier. The time point of the outlier can be given either as absolute time point or as c(a,b), i.e. at the bth 'month' of the ath 'year' where each year has frequency(x) months, assuming x is a time series. 
xtransf 
xtranf is a matrix with each column containing a covariate that affects the time series response in terms of an ARMA filter of order (p,q), i.e. if Z is one such covariate, its effect on the time series is (theta_0+theta_1B+...+theta_{q1}B^{q1})/(1phi_1 B ...phi_p B^p) Z_t In particular, if p=0 and q=1, this specifies a simple regression relationship, which should be included in xreg and not here. Note that the filter starts with zero initial values. Hence, it is pertinent to meandelete each distributedlag covariate, and this is not done automatically. 
transfer 
a list consisting of the ARMA orders for each transfer (distributed lag) covariate. 
Value
An Arimax object contining the model fit.
Author(s)
Original author of the arima function in R stats: Brian Ripley. The arimax function is based on the stats:::arima function, with modifications by KungSik Chan.
See Also
arima
Examples
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