Interactive response surface modeling
rstool opens a graphical
user interface for interactively investigating one-dimensional contours
of multidimensional response surface models.
By default, the interface opens with the data from
a fitted response surface with constant, linear, and interaction terms.
A sequence of plots is displayed, each showing a contour of
the response surface against a single predictor, with all other predictors
rstool plots a 95% simultaneous confidence
band for the fitted response surface as two red curves. Predictor
values are displayed in the text boxes on the horizontal axis and
are marked by vertical dashed blue lines in the plots. Predictor values
are changed by editing the text boxes or by dragging the dashed blue
lines. When you change the value of a predictor, all plots update
to show the new point in predictor space.
The pop-up menu at the lower left of the interface allows you to choose among the following models:
Linear— Constant and linear terms (the default)
Pure Quadratic— Constant, linear, and squared terms
Interactions— Constant, linear, and interaction terms
Full Quadratic— Constant, linear, interaction, and squared terms
Click Export to open the following dialog box:
The dialog allows you to save information about the fit to MATLAB® workspace variables with valid names.
the interface with the predictor data in
response data in
Y, and the fitted model
Distinct predictor variables should appear in different columns of
be a vector, corresponding to a single response, or a matrix, with
columns corresponding to multiple responses.
have as many elements (or rows, if it is a matrix) as
The optional input
model can be any
one of the following:
'linear'— Constant and linear terms (the default)
'purequadratic'— Constant, linear, and squared terms
'interaction'— Constant, linear, and interaction terms
'quadratic'— Constant, linear, interaction, and squared terms
To specify a polynomial model of arbitrary order, or a model
without a constant term, use a matrix for
global confidence intervals for new observations in the plots.
labels the axes using
yname. To label
each subplot differently,
yname can be
string arrays or cell arrays of character vectors.
The following uses
rstool to visualize
a quadratic response surface model of the 3-D chemical reaction data
load reaction alpha = 0.01; % Significance level rstool(reactants,rate,'quadratic',alpha,xn,yn)
rstool interface is used by
rsmdemo to visualize the results of simulated
experiments with data like that in
As described in Response Surface Designs,
a response surface model to generate simulated data at combinations
of predictors specified by either the user or by a designed experiment.
Introduced before R2006a