aic {cts} | R Documentation |
Compute t-statistic and AIC
aic(object)
object |
a fitted time-series CAR model |
For continuous CAR model selection, t-statistic and AIC are calculated
based on reparameterized coefficients phi
and covariance matrix
ecov
. From the t-statistic, the final model is chosen such that
if the true model order
is less than the large value used for
model estimation then for i > order
the deviations of the
estimated parameters phi
from their true value of 0 will be
small. From the AIC, the final model is chosen based on the smallest AIC
value.
A table with t-statistic and AIC for the corresponding model order.
This is not "true" AIC
G. Tunnicliffe Wilson and Zhu Wang
Belcher, J. and Hampton, J. S. and Tunnicliffe Wilson, G. (1994). Parameterization of continuous time autoregressive models for irregularly sampled time series data. Journal of the Royal Statistical Society, Series B, Methodological,56,141–155
## Not run: data(V22174) (fit <- car(V22174,scale=0.2,order=14)) aic(fit) ## End(Not run)