Model Browser User's Guide

Cross Section View

The cross-section view shows an array of cross sections through the model surface. You can choose the point of cross section in each factor. Data points near cross sections are displayed, and you can alter the tolerances to determine how much data is shown. The only exception is when you evaluate a model without data; in this case no data points are displayed.

The number of plots is the same as the number of input factors to the model. The plot in S shows the value of the model for a range of values of S while the other input factors (L, N, A) are held constant. Their values are displayed in the controls at the top left, and are indicated on the plots by the vertical orange bars.

• You can change the values of the input factors by dragging the orange bars on the plots, using the buttons on the controls, or by typing directly into the edit boxes.
• For example, changing the value of N to 1000 (in any of these ways) does nothing to the graph of N, but all the other factor plots now show cross sections through the model surface at N = 1000 (and the values of the other variables shown in the controls).

On the plots, the dotted lines indicate a confidence interval around the model. You define the confidence associated with these bounding lines using the Plot confidence level (%) edit box. You can toggle confidence intervals on and off using the check box on this control.

For each model displayed, the value of the model and the confidence interval around this are recorded in the legend at the lower left. The text colors match the plot colors. You can select multiple models to display in the list at the bottom using Ctrl+click, or click Select All. The values of the input factors (for which the model is evaluated) can be found in the controls (in the Input Factors pane) and seen as the orange lines on the plots.

Data points are displayed when they fall within the tolerance limit near each cross section. You can set the tolerance in the Tol edit boxes.

• For example, if N is set to 1000, and the tolerance for N is set to 500, all data points with values between N = 500 and N = 1500 appear on the plots of the other factors.
• This means that changing the tolerance in one factor affects the data points that appear on the plots of all the other factors. It does not affect the plots of that factor.
• You can click data points in the plots to see their values. Several points can mask each other; in this case the values of all coincident data points are displayed.

The following example illustrates how the tolerance level determines which data points are displayed. The tolerance for TP_REL (500) includes all points in the data set (this is an extreme example). The plot for N therefore shows the data points for all the tests. Note that you can see the structure of the data as each test shows as a vertical line of points.

You can see that the orange line on the N plot passes through a test. This orange line shows the value of N for the cross-section plot of TP_REL. You can also read the value in the edit box (N=1753.3). The tolerance for N (200) only includes data points of this test. Data in adjacent tests fall outside this tolerance. Therefore the TP_REL plot shows the data points from one test only.

Increasing the tolerance on N will mean that more data points fall within the tolerance and so would appear on the TP_REL plot.

Residuals View

MLE