Modeling and Multivariate Methods - SAS

246 Performing Nonlinear Regression Chapter 9
Nonlinear Fitting with Fit Curve
The Nonlinear platform launch window has the following features:
Y, Response Select the Y variable.
X, Predictor Formula Select either the X variable or a column containing the model formula with
parameters.
Group Specify a grouping variable. The fitted model has separate parameters for each level of the grouping
variable.
Weight
Specify a variable containing the weights of observations.
Freq
Loss
Specify a variable representing the frequency of an observation.
Specify a formula column giving a loss function.
By
Specify a variable to perform a separate analysis for every level of the variable.
Model Library Launches the Model Library tool. For more details, see “Use the Model Library” on
page 264.
The checkboxes at the bottom of the window are only for classic Nonlinear analyses:
Second Derivatives Uses second derivatives as well as first derivatives in the iterative method to find a
solution. With second derivatives, the method is called Newton-Raphson rather than Gauss-Newton.
This method is useful only if the residuals are unusually large or if you specify a custom loss function
and your model is not linear in its parameters. This option is used only when a formula column is
provided in the X, Predictor Formula role.
Numeric Derivatives Only Uses only numeric derivatives only. This option is useful when you have a
model for which it is too messy to take analytic derivatives. It can also be valuable in obtaining
convergence in tough cases. This option is used only when a formula column is provided in the X,
Predictor Formula role.
Expand Intermediate Formulas Tells JMP that if an ingredient column to the model 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. This option is used only when a formula column is provided in the X, Predictor
Formula role.
Nonlinear Fitting with Fit Curve
The platform provides several types of built-in nonlinear models: polynomials, logistic, Gompertz,
exponential growth, peak, and pharmacokinetic. To fit one of the built-in models, follow the steps below:
1. Open your data table and select Analyze > Modeling > Nonlinear.
2. On the Nonlinear launch window, assign the X variable to the X, Predictor Formula role, and the Y
variable to the Y, Response role (Figure 9.4).
3. Assign variables to other roles as needed.