arima.diag
.
The diagnostics include the autocorrelation function of the residuals,
the standardized residuals, and the portmanteau goodness of fit test statistic.
arima.diag.plot(z, layout=<<see below>>, type="h", ...)
arima.diag
,
including the components
std.resid
(or
resid
),
acf.list
, and/or
gof
.
z
.
"l"
and
"p"
.
std.resid
(or
resid
).
std.resid
is present, a plot of the standardized residuals
will be produced.
Otherwise, if
resid
is present, a plot of the raw residuals will be given.
If
acf.list
is present, then
acf.plot
will be called to produce
a plot of the autocorrelation function of the residuals
with a 95% confidence band.
If
gof
is present, then the p-values for the Portmanteau will be plotted.
The plot for
acf.list
is always high density,
and the plot for
gof
is always a point plot.
The residual plot is controlled by the
type
argument.
Box, G. E. P. and Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control. Holden-Day, Oakland, Calif. Chapter 8.
# compute and plot diagnostics for simulated AR(1) series x <- arima.sim(model=list(ar=.9)) fit <- arima.mle(x,model=list(ar=.9)) diag.fit <- arima.diag(fit) # this is equivalent to diag.fit <- arima.diag(fit,plot=F) arima.diag.plot(diag.fit)