Handle a simple list specification of pcarma models. Functions to convert to and from a representation appropriate for handing on to optimisation functions.
pcarma_prepare(model, type)
pcarma_unvec(model)
pcarma_tovec(model)
for pcarma_unvec, a list with components:
autoregressive orders, numeric vector
moving average orders, numeric vector
innovation variances
autoregressive parameters
moving average parameters
for pcarma_tovec, a list with components:
autoregressive order
moving average order
parameters of the model, a numeric vector. TODO: give the order of the parameters in the vector!
for pcarma_prepare, a list as pcarma_unvec, see also
Details.
specification of a pcarma model, a list, see Details.
not used.
Georgi N. Boshnakov
These functions work with a specification of a pcarma model as a list
with components period, p, q, param,
phi, theta and si2, see also section `Values'.
The functions do not necessarily need or examine all these components.
Argument model is a list with components as accepted by
pcarma_prepare. Details are below but the guiding rule is that
there are sensible defaults for absent components.
pcarma_prepare gives a standard representation of model, in
the sense that it ensures that the model has components period,
p and q, such that p and q are vectors of
length period. pcarma_prepare does not examine any other
components of the model. (TODO: do the same for the
innovation variance?)
If model$period is NULL, pcarma_prepare sets it to the
length of the longer of model$p and model$q. If
model$p is a scalar it is extended with rep(model$p,
period). Missing or NULL model$p is equivalent to
model$p = 0. model$q is processed analogously.
The net effect is that period, p and q will be set
as expected as long as period is given or at least one of the
other two is of length equal to the period. A warning is issued if
period <= 1 (it is all too easy to give scalar values for
p and q and forget to set the period, in which case
period will be deduced to be one).
A number of functions (including pcarma_tovec and
pcarma_unvec) dealing with the list representation of pcarma
models start by calling pcarma_prepare to avoid the need for
handling all possible cases.
pcarma_tovec returns a list with components p,
q and param, where param is a numeric vector
containing the pcarma parameters and the innovations variances and
thus is suitable for optimisation functions. Notice that it is
component param that is a vector. The reason that pcarma_tovec
returns a list, is that the caller may need to do further work before
calling a generic optimisation function. For exampe, it may wish to
dop the variances from the vector.
pcarma_unvec(model) performs the inverse operation. It takes a
list like that produced by pcarma_tovec and converts it to a
detailed list containing the components of the model.