R: Response-surface analysis

rsm-package {rsm} | R Documentation

## Response-surface analysis

### Description

The `rsm` package provides functions useful for designing and analyzing experiments that are done sequentially in hopes of optimizing a response surface.

The function `ccd` can generate (and randomize) a central-composite design; it allows the user to specify an aliasing or fractional blocking structure. The function `bbd` generates and randomizes a Box-Behnken design. The function `ccd.pick` is useful for identifying good parameter choices in central-composite designs. Functions `cube`, `star`, `foldover`, `dupe`, and `djoin` are also provided to build-up designs from individual blocks. The function `varfcn` allows the experimenter to examine the predictive capabilities of a design before collecting data.

The function `rsm` is an enhancement of `lm` that provides for additional analyses peculiar to response surfaces. It requires a model formula that contains a call to `FO` or `SO` to specify a first- or second-order model. Once the model is fitted, the `steepest` function may be used to obtain the direction of steepest ascent (or descent). `canonical.path` is an alternative to `steepest` for second-order response surfaces.

In RSM methods, appropriate coding of data is important not only for numerical stability, but for proper scaling of results; the function `coded.data` and its relatives facilitate this coding requirement.

Finally, a few more functions are provided that may be useful beyond response-surface applications. `contour.lm`, `persp.lm`, and `image.lm` aids in visualizing a response surface, or of any other `lm` object where a surface is fitted. `model.data` recovers the data used in a `lm` call, but unlike `model.frame`, no polynomials, factors, etc. are expanded.

For more information and examples, use vignette("rsm") and vignette("rs-illus"). Additionally, vignette("rsm-plots") provides some illustrations of the graphics functions.

### Author(s)

Russell V. Lenth

Maintainer: Russell V. Lenth <russell-lenth@uiowa.edu>

### References

Box, GEP, Hunter, JS, and Hunter, WG (2005) Statistics for Experimenters (2nd ed.), Wiley-Interscience.

Lenth RV (2009) “Response-Surface Methods in R, Using rsm”, Journal of Statistical Software, 32(7), 1–17. http://www.jstatsoft.org/v32/i07/.

Myers, RH, Montgomery, DC, and Anderson-Cook, CM (2009), Response Surface Methodology (3rd ed.), Wiley.

[Package rsm version 2.9 Index]