Handbook of Statistics 2: Classification, Pattern Recognition and Reduction of Dimensionality

P. R. Krishnaiah, L. N. Kanal044486217X, 9780444862174

Hardbound. Papers included in this volume deal with discriminant analysis, clustering techniques and software, multidimensional scaling, statistical, linguistic and artificial intelligence models and methods for pattern recognition and some of their applications. Further examined are the selection of subsets of variables for allocation and discrimination, and reviews of some paradoxes and open questions in the areas of variable selection, dimensionality, sample size and error estimation.

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Table of contents :
Preface……Page 1
Table of Contents……Page 6
Contributors……Page 16
1. Discriminant Analysis for Time Series……Page 18
2. Optimum Rules for Classification into Two Multivariate Normal Populations with the Same Covariance Matrix……Page 64
3. Large Sample Approximations and Asymptotic Expansions of Classification Statistics……Page 78
4. Bayesian Discrimination……Page 118
5. Classification of Growth Curves……Page 138
6. Nonparametric Classification……Page 155
7. Logistic Discrimination……Page 185
8. Nearest Neighbor Methods in Discrimination……Page 208
9. The Classification and Mixture Maximum Likelihood Approaches to Cluster Analysis……Page 213
10. Graphical Techniques for Multivariate Data and for Clustering……Page 223
11. Cluster Analysis Software……Page 259
12. Single-link Clustering Algorithms……Page 281
13. Theory of Multidimensional Scaling……Page 299
14. Multidimensional Scaling and its Applications……Page 331
15. Intrinsic Dimensionality Extraction……Page 360
16. Structural Methods in Image Analysis and Recognition……Page 374
17. Image Models……Page 396
18. Image Texture Survey……Page 411
19. Applications of Stochastic Languages……Page 428
20. A Unifying Viewpoint on Pattern Recognition……Page 461
21. Logical Functions in the Problems of Empirical Prediction……Page 488
22. Inference and Data Tables with Missing Values……Page 501
23. Recognition of Electrocardiographic Patterns……Page 509
24. Waveform Parsing Systems……Page 535
25. Continuous Speech Recognition: Statistical Methods……Page 557
26. Applications of Pattern Recognition in Radar……Page 582
27. White Blood Cell Recognition……Page 601
28. Pattern Recognition Techniques for Remote Sensing Applications……Page 614
29. Optical Character Recognition – Theory and Practice……Page 626
30. Computer and Statistical Considerations for Oil Spill Identification……Page 655
31. Pattern Recognition in Chemistry……Page 676
32. Covariance Matrix Representation and Object-Predicate Symmetry……Page 701
33. Multivariate Morphometrics……Page 722
34. Multivariate Analysis with Latent Variables……Page 747
35. Use of Distance Measures, Information Measures and Error Bounds in Feature Evaluation……Page 772
36. Topics in Measurement Selection……Page 791
37. Selection of Variables Under Univariate Regression Models……Page 802
38. On the Selection of Variables Under Regression Models Using Krishnaiah’s Finite Intersection Tests……Page 818
39. Dimensionality and Sample Size Considerations in Pattern Recognition Practice……Page 831
40. Selecting Variables in Discriminant Analysis for Improving upon Classical Procedures……Page 852
41. Selection of Variables in Discriminant Analysis……Page 877
Corrections to Handbook of Statistics, Volume 1 “Analysis of Variance”……Page 887
Subject Index……Page 889