Classification Pattern Recognition and Reduction of Dimensionality (Handbook of Statistics, Volume 2)

Oversized hardcover, third impression, xxii + 903 pages, NOT ex-library. Weight over 1.8kg. Book is clean and bright throughout, untanned, with unmarked text and secure binding, free of inscriptions and stamps. Issued without a dust jacket. -- Contents: 1. Discriminant Analysis for Time Series 2. Optimum Rules for Classification into Two Multivariate Normal Populations with the Same Covariance Matrix 3. Large Sample Approximations and Asymptotic Expansions of Classification Statistics 4. Bayesian Discrimination 5. Classification of Growth Curves 6. Nonparametric Classification 7. Logistic Discrimination 8. Nearest Neighbor Methods in Discrimination 9. The Classification and Mixture Maximum Likelihood Approaches to Cluster Analysis 10. Graphical Techniques for Multivariate Data and for Clustering 11. Cluster Analysis Software 12. Single-link Clustering Algorithms 13. Theory of Multidimensional Scaling 14. Multidimensional Scaling and its Applications 15. Intrinsic Dimensionality Extraction 16. Structural Methods in Image Analysis and Recognition 17. Image Models 18. Image Texture Survey 19. Applications of Stochastic Languages 20. A Unifying Viewpoint on Pattern Recognition 21. Logical Functions in the Problems of Empirical Prediction 22. Inference and Data Tables with Missing Values 23. Recognition of Electrocardiographic Patterns 24. Waveform Parsing Systems 25. Continuous Speech Recognition: Statistical Methods 26. Applications of Pattern Recognition in Radar 27. White Blood Cell Recognition 28. Pattern Recognition Techniques for Remote Sensing Applications 29. Optical Character Recognition: Theory and Practice 30. Computer and Statistical Considerations for Oil Spill Identification 31. Pattern Recognition in Chemistry 32. Covariance Matrix Representation and Object-Predicate Symmetry 33. Multivariate Morphometrics 34. Multivariate Analysis with Latent Variables 35. Use of Distance Measures, Information Measures and Error Bounds in Feature Evaluation 36. Topics in Measurement Selection 37. Selection of Variables Under Univariate Regression Models 38. On the Selection of Variables Under Regression Models Using Krishnaiah's Finite Intersection Tests 39. Dimensionality and Sample Size Considerations in Pattern Recognition Practice 40. Selecting Variables in Discriminant Analysis for Improving upon Classical Procedures 41. Selection of Variables in Discriminant Analysis; Corrections to Handbook of Statistics, Volume 1: Analysis of Variance; Subject Index.…