| rsm {rsm} | R Documentation |
Fit a linear model with a response-surface component, and produce appropriate analyses and summaries.
rsm (..., data) ## S3 method for class 'rsm': summary (object, ...) ## S3 method for class 'summary.rsm': print(x, ...) loftest (object)
... |
In rsm, arguments that are passed to lm.
The model must include an FO() or SO() term.to
define the response-surface portion of the model.
In summary, and print, additional arguments
are passed to their generic methods.
|
data |
Optional data.frame as in lm. This could also be
a coded.data object, in which case additional information
is included in subsequent summaries. |
object |
An object of class rsm |
x |
An object produced by summary |
In rsm, the model formula must contain at least an FO term; optionally, you can add
a TWI() term and/or a PQ() term as well (use the same variables in each!).
For convenience, specifying SO() is the same as including FO(), TWI(), and PQ(),
and is the safe, preferred way of specifying a full second-order model.
rsm returns an rsm object, which is a lm object with
additional members as follows:
order |
The order of the model: 1 for first-order, 1.5 for first-order plus interactions, or 2 for a model that contains square terms. |
b |
The first-order response-surface coefficients. |
B |
The matrix of second-order response-surface coefficients, if present. |
labels |
Labels for the response-surface terms. These make the summary much more readable. |
coding |
Coding formulas, if data is a coded.data object. |
sa |
Unit-length vector of the path of steepest ascent (first-order models only). |
canonical |
Canonical analysis (second-order models only). This is a list with elements xs, the stationary point, and eigen, the eigenanalysis
of B (see above). |
lof |
ANOVA table including lack-of-fit test. |
coding |
Coding formulas in parent rsm object. |
Its print method shows the regression summary,
followed by an ANOVA and lack-of-fit test. For first-order models, it shows the direction of
steepest ascent, and for second-order models, it shows the canonical analysis of the
response surface.
loftest returns an anova object that tests the fitted model against a model
that interpolates the means of the response-surface-variable combinations.
Russell V. Lenth
Lenth RV (2009). ``Response-Surface Methods in R, Using rsm'', Journal of Statistical Software, 32(7), 1–17. http://www.jstatsoft.org/v32/i07/.
FO, SO,
lm, summary, coded.data
library(rsm) CR = coded.data (ChemReact, x1~(Time-85)/5, x2~(Temp-175)/5) ### 1st-order model, using only the first block CR.rs1 = rsm (Yield ~ FO(x1,x2), data=CR, subset=1:7) summary(CR.rs1) ### 2nd-order model, using both blocks CR.rs2 = rsm (Yield ~ Block + SO(x1,x2), data=CR) summary(CR.rs2)