pcarma_unvec {pcts}

Functions for work with a simple list specification of pcarma models

Description

Handle a simple list specification of pcarma models. Functions to convert to and from a representation appropriate for handing on to optimisation functions.

Usage

pcarma_prepare(model, type)
pcarma_unvec(model)
pcarma_tovec(model)

Arguments

model

specification of a pcarma model, a list, see Details.

type

not used.

Details

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.

Value

for pcarma_unvec, a list with components:

p

autoregressive orders, numeric vector

q

moving average orders, numeric vector

si2

innovation variances

phi

autoregressive parameters

theta

moving average parameters

for pcarma_tovec, a list with components:

p

autoregressive order

q

moving average order

param

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.

Note

The specification and the functions were created ad hoc to get the computations going and are not always consistent with other parts of the package.

Author(s)

Georgi N. Boshnakov