ci.plot

0th

Percentile

Plot confidence and prediction intervals for simple linear regression

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.

Keywords
hplot, regression
Usage
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), ...
        )
Arguments
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 spanni
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.
Value

  • "trellis" object containing the plot.

Note

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.

See Also

lm, predict.lm

Aliases
  • ci.plot
  • ci.plot.lm
Examples
tmp <- data.frame(x=rnorm(20), y=rnorm(20))
tmp.lm <- lm(y ~ x, data=tmp)
ci.plot(tmp.lm)
Documentation reproduced from package HH, version 2.3-42, License: GPL (>= 2)

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