ctsdiag {cts}R Documentation

Diagnostic Plots for Time-Series CAR Fits

Description

A generic function to plot time-series diagnostics.

Usage

ctsdiag(object, gof.lag = 10, ...)

Arguments

object a fitted time-series CAR model
gof.lag the maximum number of lags for a Portmanteau goodness-of-fit test
... further arguments to be passed to particular methods

Details

This is a generic function. It will generally plot the residuals, often standadized, the autocorrelation function of the residuals, and the p-values of a Portmanteau test for all lags up to gof.lag.

The method for car object plots residuals scaled by the estimate of their (individual) variance, and use the Ljung–Box version of the portmanteau test.

Value

None. Diagnostics are plotted.

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

Jones, Richard H. (1981). Fitting a continuous time autoregression to discrete data. Applied Time Series Analysis II, 651–682

Wang, Zhu(2004). The Application of the Kalman Filter to Nonstationary Time Series through Time Deformation. PhD thesis, Southern Methodist University

See Also

car

Examples

## Not run: 
data(V22174)
(fit <- car(V22174,scale=0.2,order=7))
ctsdiag(fit)
## End(Not run)

[Package cts version 1.0 Index]