ctsdiag {cts} | R Documentation |
A generic function to plot time-series diagnostics.
ctsdiag(object, gof.lag = 10, ...)
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 |
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.
None. Diagnostics are plotted.
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
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
## Not run: data(V22174) (fit <- car(V22174,scale=0.2,order=7)) ctsdiag(fit) ## End(Not run)