Note: It is possible to create a factors table by entering data into an empty table, but remember to assign each column an appropriate Design Role. Do this by right-clicking on the column name in the data grid and selecting Column Properties > Design Role. In the Design Role area, select the appropriate role.
In the constraint table, the first rows contain the coefficients for each factor. The last row contains the inequality bound. Each constraint’s column contains a column property called ConstraintState that identifies the constraint as a “less than” or a “greater than” constraint. See ConstraintState in Column Properties.
To reproduce a design or simulated responses, enter the random seed that generated them. For designs using random starts, set the seed before clicking Make Design. To control simulated responses or run order, set the seed before clicking Make Table.
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A script called DOE Simulate is saved to the design table. This script reopens the Model window, enabling you to re-simulate values or to make changes to the simulated response distribution.
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Make selections in the Model window to control the distribution of simulated response values. When you click Apply, a formula for the simulated response values is saved in a new column called <Y> Simulated, where Y is the name of the response. Clicking Apply again updates the formula and values in <Y> Simulated.
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You can use Simulate Responses to conduct simulation analyses using the JMP Pro Simulate feature. For more information and DOE examples, see Simulate in the Basic Analysis book.
You can use Simulate Responses to conduct simulation analyses using the JMP Pro Simulate feature. For more information and DOE examples, see Simulate in the Basic Analysis book.Saves scripts called Moments Matrix and Model Matrix to the design data table. These scripts contain the moments and design matrices. See Save X Matrix in Custom Designs.
Caution: For a design with nominal factors, the matrix in the Model Matrix script saved by the Save X Matrix option is not the coding matrix used in fitting the linear model. You can obtain the coding matrix used for fitting the model by selecting the option Save Columns > Save Coding Table in the Fit Model report that you obtain when you run the Model script.
Changes the design optimality criterion. The default criterion, Recommended, specifies D-optimality for all design types, unless you added quadratic effects using the RSM button in the Model outline. For more information about the D-, I-, and alias-optimal designs, see Optimality Criteria in Custom Designs.
Note: You can set a preference to always use a given optimality criterion. Select File > Preferences > Platforms > DOE. Select Optimality Criterion and choose your preferred criterion.
Enables you to specify the number of random starts used in constructing the design. See Number of Starts in Custom Designs.
Maximum number of seconds spent searching for a design. The default search time is based on the complexity of the design. See Design Search Time in Custom Designs and Number of Starts in Custom Designs.
If the iterations of the algorithm require more than a few seconds, a Computing Design progress window appears. If you click Cancel in the progress window, the calculation stops and gives the best design found at that point. The progress window also displays D-efficiency for D-optimal designs that do not include factors with Changes set to Hard or Very Hard or with Estimability set to If Possible.
Note: You can set a preference for Design Search Time. Select File > Preferences > Platforms > DOE. Select Design Search Time and enter the maximum number of seconds. In certain situations where more time is required, JMP extends the search time.
Constrains the continuous factors in a design to a hypersphere. Specify the radius and click OK. Design points are chosen so that their distance from 0 equals the Sphere Radius. Select this option before you click Make Design.
Bayesian D- or I-optimality is used in constructing designs with If Possible factors. The default values used in the algorithm are 0 for Necessary terms, 4 for interactions involving If Possible terms, and 1 for If Possible terms. For more details, see The Alias Matrix in Technical Details and Optimality Criteria in Custom Designs.
For the definition of D-efficiency, see Optimality Criteria in Custom Designs. For details about alias optimality, see Alias Optimality in Custom Designs.