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, and does a sanity check to make sure it is suitable for estimating a second-order model. 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.

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 nyumerical stability, but for proper scaling of results; the function coded.data and its relatives facilitate this coding requirement.

Finally, two more functions are provided that may be useful beyond response-surface applications. contour.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")

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.

Meyers, RH and Montgomery, DC (2002), Response Surface Methodology (2nd ed.), Wiley-Interscience.


[Package rsm version 1.11 Index]