Shows or hides the confidence intervals. The intervals are drawn by bars for categorical factors, and curves for continuous factors. These are available only when the profiler is used inside certain fitting platforms.
Shows or hides a purple triangle whose height and direction correspond to the value of the partial derivative of the profile function at its current value (see Sensitivity Indicators). This is useful in large profiles to be able to quickly spot the sensitive cells.
Sets the current factor values to maximize the desirability functions. Takes into account the response importance weights.
Used only if one or more factors are locked. The ranges of the locked factors are divided into a grid, and the desirability is maximized at each grid point. This is useful if the model that you are profiling has categorical factors. Then the optimal condition can be found for each combination of the categorical factors.
Saves the three desirability function settings for each response, and the associated desirability values, as a Response Limits column property in the data table. These correspond to the coordinates of the handles in the desirability plots.
Creates a column in the data table with a formula for Desirability. The formula uses the fitting formula when it can, or the response variables when it cannot access the fitting formula.
Displays a window for each factor allowing you to enter a specific value for the factor’s current setting, to lock that setting, and to control aspects of the grid. See the section for details.
Remember Settings adds an outline node to the report that accumulates the values of the current settings each time the Remember Settings command is invoked. Each remembered setting is preceded by a radio button that is used to reset to those settings.
Copy Settings Script and Paste Settings Script enable you to move the current Profiler’s settings to a Profiler in another report.
Append Settings to Table appends the current profiler’s settings to the end of the data table. This is useful if you have a combination of settings in the Profiler that you want to add to an experiment in order to do another run.
Link Profilers links all the profilers together. A change in a factor in one profiler causes that factor to change to that value in all other profilers, including Surface Plot. This is a global option, set or unset for all profilers.
Set Script sets a script that is called each time a factor changes. The set script receives a list of arguments of the form:
Then enter ProfileCallbackLog in the Set Script dialog.
Produces a new data table with columns for the factors that contain grid values, columns for each of the responses with computed values at each grid point, and the desirability computation at each grid point.
If you have a lot of factors, it is impractical to use the Output Grid Table command, because it produces a large table. A memory allocation message might display for large grid tables. In such cases, you should lock some of the factors, which are held at locked, constant values. To get the window to specify locked columns, ALT- or Option-click inside the profiler graph to get a window that has a Lock Factor Setting check box.
Prompts for a number of runs and creates an output table with that many rows, with random factor settings and predicted values over those settings. This is equivalent to (but much simpler than) opening the Simulator, resetting all the factors to a random uniform distribution, then simulating output. This command is similar to Output Grid Table, except it results in a random table rather than a sequenced one.
The prime reason to make uniform random factor tables is to explore the factor space in a multivariate way using graphical queries. This technique is called Filtered Monte Carlo.
Suppose you want to see the locus of all factor settings that produce a given range to desirable response settings. By selecting and hiding the points that do not qualify (using graphical brushing or the Data Filter), you see the possibilities of what is left: the opportunity space yielding the result that you want.
Some rows may appear selected and marked with a red dot. These represent the points on the multivariate desirability Pareto Frontier - the points that are not dominated by other points with respect to the desirability of all the factors.
Enables you to add, change, or delete linear constraints. The constraints are incorporated into the operation of Prediction Profiler. See .
Enables you to set the default number of levels for each continuous factor. This option is useful when the Profiler is especially large. When calculating the traces for the first time, JMP measures how long it takes. If this time is greater than three seconds, you are alerted that decreasing the Default N Levels speeds up the calculations.
Appears when random effects are included in the model. The random effects predictions are used in formulating the predicted value and profiles.
Launches the Simulator. The Simulator enables you to create Monte Carlo simulations using random noise added to factors and predictions for the model. A typical use is to set fixed factors at their optimal settings, and uncontrolled factors and model noise to random values. You then find out the rate of responses outside the specification limits. For details see the Simulator section.
Brings up interaction plots that are interactive with respect to the profiler values. This option can help visualize third degree interactions by seeing how the plot changes as current values for the terms are changed. The cells that change for a given term are the cells that do not involve that term directly.
Enter the number of plots that appear in a row. This option helps you view plots vertically rather than in one wide row.
Re-scales the Y axis if the response is outside the axis range, so that the range of the response is included.