optOrd  R Documentation 
From a matrix with values of an information criterion for different orders
p
and q
of an autoregressivemovingaverage (ARMA) model, the
optimal orders are selected.
optOrd(mat, restr = NULL, sFUN = min)
mat 
a numeric matrix, whose rows represent the AR orders

restr 
a single expression (not a character object) that defines
further restrictions; the standard logical operators, e.g. 
sFUN 
the selection function; is set to 
Given a matrix mat
filled with the values of an information criterion
for different estimated ARMA(p,q
) models, where the rows represent
different orders p = 0, 1, ..., p_{max}
and where
the columns represent the orders q = 0, 1, ..., q_{max}
, the function returns a vector with the optimal orders
p
and q
. Further selection restrictions can be passed to the
argument restr
as an expression. To implement a restriction, the rows
and columns are addressed via p
and q
, respectively. Moreover,
standard boolean operators such as ==
, >=
or &
can be
used. See the Section Examples for examples of different restrictions.
In many cases, the minimum value of a criterion is considered to indicate
the best model. However, in some other cases a different selection approach
might be appropriate. Therefore, a selection function can be considered by
means of the argument sFUN
. The default is sFUN = min
, i.e. the
function min
is applied to select the optimal
orders.
The function returns a vector with two elements. The first element is the
optimal order p
, whereas the second element is the selected optimal
order q
.
Sebastian Letmathe (Scientific Employee) (Department of Economics,
Paderborn University),
## Not run:
set.seed(21)
Xt < arima.sim(model = list(ar = c(1.2, 0.5), ma = 0.7), n = 1000) + 7
mat < smoots::critMatrix(Xt)
optOrd(mat) # without restrictions
optOrd(mat, p <= q) # with one restriction
optOrd(mat, p >= 1 & q >= 4) # with two restrictions
## End(Not run)
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