Modeling and Multivariate Methods - SAS

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692 Index Ellipses Transparency 451 EM algorithm 469 Emphasis 50 EMS (Traditional) 118 EMS method 69 Enter All 140 Entered 143 Entropy RSquare 633 epsilon adjustment 169 Equamax 489 Equivalence Test 113, 255 Error 59–60 error matrix 166 Estimate 60, 90, 143, 260, 363, 366, 379 Estimate Nugget Parameter 295 Estimates 68, 70, 76, 81–88 Even Spacing 466 evolution 377 Exact F 167 Excel profiling models stored in 622 Excluded Effect 46 excluded rows 59 Exercise.jmp 164 Expand Intermediate Formulas 557, 575 Expand Into Categories, selecting column 257 Expanded Estimates 66, 68 Expectation Maximization algorithm 469 expectation step 461 exponential smoothing see Smoothing Models Expression 594 F F Ratio 60, 62, 64 F Ratio in quotes 144 F test, joint 69 Factor 363 factor analysis 483 factor model 656–672 Factor Rotation 486 Factor Settings 565, 591 Factorial Sorted 41 Factorial to Degree 41 Factorparsimax 489 failure3Delimited.jmp 389 Failure3Freq.jmp 388 failure3Freq.jmp 397 failure3ID.jmp 390 failure3Indicators.jmp 389 failure3MultipleField.jmp 391 fiducial confidence limits 72 Fieller’s method 72 Filtered Monte Carlo 566 First 274 Firth Bias-adjusted Estimates 430 Fish Patty.jmp 583 Fisher’s Kappa 358 Fit Curve 247–252 Fit Group 52, 625 Fit Model Transformations 48 Fit Model data table script 33 Fit Model platform 147, 224, 658 analysis of covariance 38, 128 analysis of variance 37, 126 effects attributes 39–48 effects buttons 39–40 effects macros 41 Emphasis 50 example 43–45, 70–73, 93, 117–118, 570–571, 577–579 expanded estimates 66 launch window 50 logistic regression 197 multiple regression 37 nested model 38 other options 50 polynomial regression 37 power analysis 75 random effects 114 repeated measures 39 response surface 39 row diagnostics 100–101 simple regression 37 SLS prediction equation 92 split-plot 39 stepwise regression categorical terms 146–147 validity check 52 Fit Y by X platform 197, 221 Fitness.jmp 135 fitting machines 674 fitting principles 653–656 Five Factor Mixture.jmp 586 Fixed 593 Fixed 378 Flash object in Profiler 562 Football.jmp 146
Index 693 forecast 351, 359–381 Forecast Periods 353, 364 Forecast plot 364 formulas used in JMP calculations 651–687 Forward 139 Freq role 199 Frequency 358 frequency data table 226 Full 202 Full Factorial 41, 215 G Gaussian 295 Gaussian Process 293 Gaussian Process 295 Gauss-Newton method 273 Generalized Linear Model 49 Generalized RSquare 633 Geometric Spacing 466 G-G 169 Go 86, 140, 142, 263, 270, 328 goal SSE 271 Golf Balls.jmp 157 Goodness of Fit test 203 Graph 355, 360 Graph Updating 578 Greenhouse-Geisser 169 Grid Density 578 group similar rows see Cluster platform H H matrix 159, 166, 173, 681 Half Normal plot 233, 235 Hardware Acceleration 550 Hats 105 Helmert 161, 169 heredity restriction, stepwise 137 Hessian 273 H-F 169 hidden column 309 Hierarchical 462 hierarchical effects 147 Hoeffding’s D 449, 456 Holt smoothing 380 homogeneity of slopes 131 Hotelling-Lawley Trace 167 Hourly 353 Huynh-Feldt 169 hypothesis 676 hypothesis SSCP matrix 166 hypothesis test 660–666, 669 I Identity 161 Indicator Group 387 Indiv Confidence Inteval 311 Individ Confidence Interval 105 Ingots.jmp 199, 208, 226 Ingots2.jmp 226, 269 InjectionMolding.jmp 306 interaction effect 63, 144, 558, 658 Interaction Plots 96–97 Interaction Profiler 566 Intercept 367 intercept 363 Inverse Corr table 446 inverse correlation 446, 457 Inverse Prediction 70–73, 208 inverse prediction 686–687 Invertible 363 Iris.jmp 162, 474, 493 Isosurface 542 item reliability 453–454 Iter 365 Iteration History 365 Iteration History report 201, 365, 654 Iteration Log 262 J jackknife 452 Jackknife Distances 451 JMP Starter 28 JMP tutorials 27 joint F test 69 Joint Factor Tests 414, 419 K K Fold Crossvalidation 327 Kendall’s Tau 449 Kendall’s tau-b 455 key concepts 674 KMeans 469 K-Means Clustering Platform SOMs 477 Technical Details 479 Knotted Spline Effect 46 Knotted Splines
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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 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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Contents Overview of the Partial Le
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Contents Introduction to Item Respo
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Contents Surface Plots . . . . . .
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538 Plotting Surfaces Chapter 23 La
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544 Plotting Surfaces Chapter 23 Th
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546 Plotting Surfaces Chapter 23 Th
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548 Plotting Surfaces Chapter 23 Pl
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550 Plotting Surfaces Chapter 23 Pl
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552 Plotting Surfaces Chapter 23 Ke
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Contents Introduction to Profiling
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556 Visualizing, Optimizing, and Si
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630 Comparing Model Performance Cha
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640 References Becker, R.A. and Cle
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Page 654 and 655: 654 Statistical Details Appendix A
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Modeling and Multivariate Methods - SAS

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