Modeling and Multivariate Methods - SAS

262 Performing Nonlinear Regression Chapter 9
Fit a Custom Model
Plot Shows or hides a plot of the X and Y variables for models with only one X variable. The model shown
on the plot is based on the current values of the parameters. To change the current values of the
parameters, use the sliders or edit boxes beneath the plot. If you specify a Group variable at launch, then
a curve shows for each group.
Iteration Options Specifies options for the fitting algorithm.
Iteration Log records each step of the fitting process in a new window.
Numeric Derivatives Only is useful when you have a model that is too messy to take analytic derivatives
for. It can also be valuable in obtaining convergence in tough cases.
Expand Intermediate Formulas tells JMP that if an ingredient column to the formula is a column that
itself has a formula, to substitute the inner formula, as long as it refers to other columns. To prevent an
ingredient column from expanding, use the Other column property with a name of "Expand Formula"
and a value of 0.
Newton chooses whether Gauss-Newton (for regular least squares) or Newton-Raphson (for models
with loss functions) is the optimization method.
QuasiNewton SR1 chooses QuasiNewton SR1 as the optimization method.
QuasiNewton BFGS chooses QuasiNewton BFGS as the optimization method.
Accept Current Estimates tells JMP to produce the solution report with the current estimates, even if
the estimates did not converge.
Show Derivatives shows the derivatives of the nonlinear formula in the JMP log. See “Notes
Concerning Derivatives” on page 273, for technical information about derivatives.
Unthreaded runs the iterations in the main computational thread. In most cases, JMP does the
computations in a separate computational thread. This improves the responsiveness of JMP while doing
other things during the nonlinear calculations. However, there are some isolated cases (models that have
side effects that call display routines, for example) that should be run in the main thread, so this option
should be turned on.
Profilers Provides various profilers for viewing response surfaces.
Profiler brings up the Prediction Profiler. The Profiler lets you view vertical slices of the surface across
each x-variable in turn, as well as find optimal values of the factors.
Contour Profiler brings up the Contour Profiler. The Contour profiler lets you see two-dimensional
contours as well as three dimensional mesh plots.
Surface Profiler creates a three-dimensional surface plot. This option is available only for models with
two or more X variables.
Parameter Profiler brings up the Prediction Profiler and profiles the SSE or loss as a function of the
parameters.
Parameter Contour Profiler brings up the Contour Profiler and contours the SSE or loss as a function
of the parameters.
Parameter Surface Profiler creates a three-dimensional surface plot and profiles the SSE or loss as a
function of the parameters. This option is available only for models with two or more parameters.