scb Simultaneous Confidence Bands scb

## Usage:

scb(x, ..., mg, flim, type)

## Description:

scb is implemented as a front-end to locfit, to compute simultaneous confidence bands using the tube formula method and extensions, based on Sun and Loader (1994).

Some examples can also be found at http://sun.cwru.edu/~jiayang/sci3.html.

## Arguments:

x
A numeric vector or matrix of predictors (as in locfit.raw), or a model formula (as in locfit).
...
mg
The scb() function evaluates the confidence bands on a grid of points, rather than the default structures used by locfit. mg controls the number of grid points. Default 10.
flim
As in locfit.raw, this defaults to the interval (or bounding box, in more than one dimension) covering the data. The confidence bands are simultaneous over this interval.
type
Type of confidence bands. type=0 computes pointwise 95% bands. type=1 computes basic simultaneous bands with no corrections. type=2,3,4 are the centered and corrected bands for parametric regression models listed in Table 3 of Sun, Loader and McCormick (2000).

## Value:

A list containing the evaluation points, fit, standard deviations and upper and lower confidence bounds. The class is "scb"; methods for printing and ploting are provided.

locfit, print.scb, plot.scb.

## Examples:

```
# corrected confidence bands for a linear logistic model
data(insect)
fit <- scb(deaths ~ lconc, type=4, w=nins, data=insect,
deg=1, family="binomial", kern="parm")
plot(fit)
```

## References:

Sun J. and Loader, C. (1994). Simultaneous confidence bands in linear regression and smoothing. \emphThe Annals of Statistics 22, 1328-1345.

Sun, J., Loader, C. and McCormick, W. (2000). Confidence bands in generalized linear models. \emphThe Annals of Statistics 28, 429-460.

htest

## Key Words:

smooth
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