aic {cts}R Documentation

Model Selection Statistics

Description

Compute t-statistic and AIC

Usage

aic(object)

Arguments

object a fitted time-series CAR model

Details

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.

Value

A table with t-statistic and AIC for the corresponding model order.

Note

This is not "true" AIC

Author(s)

G. Tunnicliffe Wilson and Zhu Wang

References

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

See Also

car

Examples

## Not run: 
data(V22174)
(fit <- car(V22174,scale=0.2,order=14))
aic(fit)
## End(Not run)

[Package cts version 1.0 Index]