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

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

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.

Included in series
Handbook of Statistics

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Published: March 1983

Imprint: North-holland

ISBN: 978-0-444-86217-4

Reviews

  • The formula of the book is really excellent: and each module is written by a known expert in the assigned topic. Such a choice of the editors makes the book readable to many potential users, both pure methodologists and applied statisticians.
    European Journal of Operational Research


    This volume, the previous volume, and the other volumes in preparation in the Handbook of Statistics series will certainly constitute a valuable aid and source of reference.
    Journal of the American Statistical Association

Contents

  • Discriminant Analysis for Time Series (R.H. Shumway). Optimum Rules for Classification into Two Multivariate Normal Populations with the Same Covariance Matrix (S. D. Gupta). Large Sample Approximations and Asymptotic Expansions of Classification Statistics (M. Siotani). Bayesian Discrimination (S. Geisser). Classification of Growth Curves (J.C. Lee). Nonparametric Classification (J.D. Broffitt). Logistic Discrimination (J.A. Anderson). Nearest Neighbor Methods in Discrimination (L. Devroye, T.J. Wagner). The Classification and Mixture Maximum Likelihood Approaches to Cluster Analysis (G.J. McLachlan). Graphical Techniques for Multivariate Data and for Clustering (J.M. Chambers, B. Kleiner). Cluster Analysis Software (R.K. Blashfield, M.S. Aldenderfer, L.C. Morey). Single-link Clustering Algorithms (F.J. Rohlf). Theory of Multidimensional Scaling (J. de Leeuw, W. Heiser). Multidimensional Scaling and its Applications (M. Wish, J.D. Carroll). Intrinsic Dimensionality Extraction (K. Fukunaga). Structural Methods in Image Analysis and Recognition (L.N. Kanal, B.A. Lambird, D. Lavine). Image Models (N. Ahuja, A. Rosenfeld). Image Texture Survey (R.M. Haralick). Applications of Stochastic Languages (K.S. Fu). A Unifying Viewpoint on Pattern Recognition (J.C. Simon, E. Backer, J. Sallentin). Logical Functions in the Problems of Empirical Prediction (G.S. Lbov). Inference and Data Tables with Missing Values (N.G. Zagoruiko, V.N. Yolkina). Recognition of Electrocardiographic Patterns (J.H. van Bemmel). Waveform Parsing Systems (C.G. Stockman). Continuous Speech Recognition: Statistical Methods (F. Jelinek, R.L. Mercer, L.R. Bahl). Applications of Pattern Recognition in Radar (A. Grometstein, W.H. Schoendorf). White Blood Cell Recognition (E.S. Gelsema, G.H. Landeweerd). Pattern Recognition Techniques for Remote Sensing Applications (P.H. Swain). Optical Character Recognition - Theory and Practice (G. Nagy). Computer and Statistical Considerations for Oil Spill Identification (Y.T. Chien, T.J. Killeen). Pattern Recognition in Chemistry (B.R. Kowalski, S. Wold). Covariance Matrix Representation and Object-Predicate Symmetry (T. Kaminuma, S. Tomita, S. Watanabe). Multivariate Morphometrics (P.A. Reyment). Multivariate Analysis with Latent Variables (P.M. Bentler, D.G. Weeks). Use of Distance Measures, Information Measures and Error Bounds in Feature Evaluation (M. Ben-Bassat). Topics in Measurement Selection (J.M. Van Campenhout). Selection of Variables under Univariate Regression Models (P.R. Krishnaiah). On the Selection of Variables under Regression Models using Krishnaiah's Finite Intersection Tests (J.L. Schmidhammer). Dimensionality and Sample Size Considerations in Pattern Recognition Practice (A.K. Jain, B. Chandrasekaran). Selecting Variables in Discriminant Analysis for Improving upon Classical Procedures (W. Schaafsma). Selection of Variables in Discriminant Analysis (P.R. Krishnaiah). Index.

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