select_order {MSinference} | R Documentation |
Calculates different information criterions for a single time series
or multiple time series with AR(p
) errors
based on the long-run variance estimator(s) for a range of tuning
parameters and different orders p
.
Description
This function fits AR(1), ... AR(9) models for all given time series and calculates different information criterions (FPE, AIC, AICC, SIC, HQ) for each of these fits. The result is the best fit in terms of minimizing the infromation criteria.
Usage
select_order(data, q = NULL, r = 5:15)
Arguments
data |
One or a number of time series in a matrix. Column names of the matrix should be reasonable |
q |
A vector of integers that consisits of different tuning
parameters to analyse. If not supplied, q is taken to be
|
r |
A vector of integers that consisits of different tuning
parameters r_bar for |
Value
A list with a number of elements:
orders |
A vector of chosen orders of length equal to the number
of time series.
For each time series the order is calculated as
|
... |
Matrices with the orders that were selected
(among |