random_regime {uGMAR} | R Documentation |
Create random regime parameters
Description
random_regime
generates random regime parameters.
Usage
random_regime(
p,
mu_scale,
sigma_scale,
restricted = FALSE,
constraints = NULL,
m,
forcestat = FALSE
)
Arguments
p |
a positive integer specifying the autoregressive order of the model. |
mu_scale |
a real valued vector of length two specifying the mean (the first element) and standard deviation (the second element)
of the normal distribution from which the |
sigma_scale |
a positive real number specifying the standard deviation of the (zero mean, positive only by taking absolute value)
normal distribution from which the component variance parameters are generated in the random mutations in the genetic algorithm.
Default is |
restricted |
a logical argument stating whether the AR coefficients |
constraints |
specifies linear constraints imposed to each regime's autoregressive parameters separately.
The symbol |
m |
which regime? This is required for models with constraints for which a list of possibly differing constraint matrices is provided. |
forcestat |
use the algorithm by Monahan (1984) to force stationarity on the AR parameters (slower)? Not supported for constrained models. |
Details
If forcestat==TRUE
, then the AR coefficients are relatively large, otherwise they are usually relatively small.
Value
- Regular models:
\upsilon_{m}
=(\phi_{m,0},
\phi_{m}
,\sigma_{m}^2)
where\phi_{m}
=(\phi_{m,1},...,\phi_{m,p})
.- Restricted models:
Not supported!
- Constrained models:
Replace the vectors
\phi_{m}
with vectors\psi_{m}
.
References
Monahan J.F. 1984. A Note on Enforcing Stationarity in Autoregressive-Moving Average Models. Biometrica 71, 403-404.