ci.plot {HH} | R Documentation |
The data, the least squares line, the confidence interval lines, and the
prediction interval lines for a simple
linear regression (lm(y ~ x)
) are displayed. Tick marks are
placed at the location of xbar, the x-value of the narrowest interval.
ci.plot(lm.object, ...) ## S3 method for class 'lm': ci.plot(lm.object, xlim=range(data[, x.name]), newdata, conf.level=.95, data=model.frame(lm.object), newfit, ylim, pch=16, main.cex=1, main=list(paste(100*conf.level, "% confidence and prediction intervals for ", substitute(lm.object), sep=""), cex=main.cex), ... )
lm.object |
Linear model for one y and one x variable. |
xlim |
xlim for plot. Default is based on data from which
lm.object was constructed. |
newdata |
data.frame containing data for which predictions
are wanted. The variable name of the column must be identical to
the name of the predictor variable in the model object.
Defaults to a data.frame containing a vector
spanning the range of observed data. User-specified values are
appended to the default vector. |
conf.level |
Confidence level for intervals, defaults to .95 |
data |
data extracted from the lm.object |
newfit |
Constructed data.frame containing the
predictions,confidence interval, and prediction interval
for the newdata . |
ylim |
ylim for plot. Default is based on the
constructed prediction interval. |
pch |
Plotting character for observed points. |
main.cex |
Font size for main title. |
main |
Main title for plot |
... |
Additional arguments to be passed to panel function. |
"trellis"
object containing the plot.
The predict.lm
functions in S-Plus and R differ.
The S-Plus function can produce both confidence and prediction
intervals with a single call. The R function produces only one
of them in a single call. Therefore the default calculation of
newfit
within the function depends on the system.
Richard M. Heiberger <rmh@temple.edu>
tmp <- data.frame(x=rnorm(20), y=rnorm(20)) tmp.lm <- lm(y ~ x, data=tmp) ci.plot(tmp.lm)