Modeling and Multivariate Methods - SAS

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546 Plotting Surfaces Chapter 23 The Surface Plot Control Panel Figure 23.9 Activated X and Y Grids Dependent Variables The dependent variables controls change depending on whether you have selected Sheet, points or Isosurface in the Appearance Controls. Controls for Sheet, Points The Dependent Variables controls are shown in Figure 23.10 with its default menus. Figure 23.10 Dependent Variable Controls Formula lets you pick the formula(s) to be displayed in the plot as surfaces. Point Response Column lets you pick the column that holds values to be plotted as points. Style menus appear after you have selected a Point Response Column. The style menu lets you choose how those points are displayed, as Points, Needles, a Mesh, Surface, or Off (not at all). Points shows individual points, which change according to the color and marker settings of the row in the data table. Needles draws lines from the x-y plane to the points, or, if a surface is also plotted, connects the surface to the points. Mesh connects the points into a triangular mesh. Surface overlays a smooth, reflective surface on the points.
Chapter 23 Plotting Surfaces 547 Plot Controls and Settings Surface enables you to show or hide the top or bottom of a surface. If Above only or Below only is selected, the opposite side of the surface is darkened. Grid slider and checkbox activate a grid for the dependent variable. Use the slider to adjust the value where the grid is drawn, or type the value into the Grid Value box above the slider. Controls for Isosurface Most of the controls for Isosurface are identical to those of Sheet, points. Figure 23.11 shows the default controls, illustrating the slightly different presentation. Figure 23.11 Dependent Variable Controls for Isosurfaces Sliders adjust the surface Dependent Variable Menu Options There are several options for the Dependent Variable, accessed through the popup menu. Formula Surface Points reveals or hides the Formula drop-down list. reveals or hides the Surface drop-down list. reveals or hides the Point Response Column drop-down list. Response Grid reveals or hides the Grid controls. Plot Controls and Settings Rotate The plot can be rotated in any direction by dragging it. Place the cursor anywhere on the plot where the cursor has a circular arrow attached to it, then click and drag the plot to rotate.
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Version 10 Modeling and Multivariat
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INDIRECT OR CONSEQUENTIAL DAMAGES O
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6 Emphasis Options for Standard Lea
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8 Models with Crossed, Interaction,
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10 8 Analyzing Screening Designs Us
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12 Examining the Residuals . . . .
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14 Response Frequencies . . . . . .
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16 19 Analyzing Principal Component
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18 Interpreting the Profiles . . .
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20 Discriminant Analysis . . . . .
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Contents Book Conventions. . . . .
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24 Learn about JMP Chapter 1 Book C
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26 Learn about JMP Chapter 1 Book C
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28 Learn about JMP Chapter 1 Additi
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30 Learn about JMP Chapter 1 Additi
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Contents Launch the Fit Model Platf
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34 Introduction to the Fit Model Pl
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Contents Example Using Standard Lea
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56 Fitting Standard Least Squares M
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Contents Overview of Stepwise Regre
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136 Fitting Stepwise Regression Mod
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Contents Example of a Multiple Resp
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158 Fitting Multiple Response Model
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Contents Overview of Generalized Li
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180 Fitting Generalized Linear Mode
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Contents Introduction to Logistic M
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200 Performing Logistic Regression
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Contents Overview of the Screening
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232 Analyzing Screening Designs Cha
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Contents Introduction to the Nonlin
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244 Performing Nonlinear Regression
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Contents Overview of Neural Network
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280 Creating Neural Networks Chapte
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Contents Launching the Platform. .
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296 Modeling Relationships With Gau
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Contents Overview of the Loglinear
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306 Fitting Dispersion Effects with
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Contents Introduction to Partitioni
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318 Recursively Partitioning Data C
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Contents Launch the Platform . . .
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354 Performing Time Series Analysis
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Contents The Categorical Platform .
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386 Performing Categorical Response
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Contents Introduction to Choice Mod
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404 Performing Choice Modeling Chap
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Contents Launch the Multivariate Pl
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444 Correlations and Multivariate T
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Contents Introduction to Clustering
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462 Clustering Data Chapter 18 The
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464 Clustering Data Chapter 18 Hier
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470 Clustering Data Chapter 18 K-Me
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472 Clustering Data Chapter 18 K-Me
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474 Clustering Data Chapter 18 Norm
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476 Clustering Data Chapter 18 Norm
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478 Clustering Data Chapter 18 Self
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480 Clustering Data Chapter 18 Self
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Contents Principal Components. . .
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484 Analyzing Principal Components
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Contents Introduction . . . . . . .
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494 Performing Discriminant Analysi
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640 References Becker, R.A. and Cle
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642 References Draper, N. and Smith
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644 References Hooper, J. H. and Am
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646 References Matsumoto, M. and Ni
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648 References Rawlings, J.O. (1988
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650 References Umetrics (1995), Mul
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Contents The Response Models . . .
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654 Statistical Details Appendix A
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690 Index Birth Death Subset.jmp 46
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692 Index Ellipses Transparency 451
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694 Index test for curvature 46 Kru
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696 Index Customizing 267 Nonlinear
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698 Index reliability analysis 453-
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700 Index Stable 363 Stable Inverti
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702 Index
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Modeling and Multivariate Methods - SAS

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