Diagnostic plots for elements of class "TML". Three plots (selectable by which) are currently available:
a residual Q-Q plot, a plot of response against fitted values and a plot of standardized residuals against fitted values.
Usage
## S3 method for class 'TML'
plot(x, which = 1:3, caption = c("Residual QQ-plot",
"Response vs. Fitted Values", "Standardized Residuals vs. Fitted Values"),
panel = points, sub.caption = deparse(x$call$formula), main = "",
ask = prod(par("mfcol")) < length(which) && dev.interactive(), ...)
Arguments
x
An object of class "TML", usually, a result of a call to TML.noncensored or TML.censored.
which
If a subset of the plots is required, specify a subset of the numbers 1:3.
caption
Caption for the different plots.
panel
Panel.
sub.caption
Sub titles.
main
Main title.
ask
If ask=TRUE, plot.TML() operates in interactive mode.
...
Optional arguments for par.
Details
The residual Q-Q plot is build with respect to the errors argument of the object.
This means that the expected order statistics are calculated either for a Gaussian or a log-Weibull distribution.
The two horizontal dotted lines on the first and the third plots represent the upper and lower cut-off values for outlier rejection.
Observations that were not retained for the estimation (outliers) are identified on the third plot.
See Also
TML.noncensored, TML.censored, plot.default
Examples
## Not run:
data(D243)
Cost <- D243$Cost # Cost (Swiss francs)
LOS <- D243$LOS # Length of stay (days)
Adm <- D243$Typadm; Adm <- (Adm==" Urg")*1 # Type of admission
# (0=on notification, 1=Emergency)
# Truncated maximum likelihood regression with log-Weibull errors
w <- TML.noncensored(log(Cost)~log(LOS)+Adm, errors="logWeibull",
otp="adaptive", control=list(fastS=TRUE))
plot(w)
plot(w, which = 1)
plot(w, which = 2)
plot(w, which = 3)
## End(Not run)