Discrete Discriminant Analysis

Discrete Discriminant Analysis

Author: Matthew Goldstein

Publisher: John Wiley & Sons

Published: 1978

Total Pages: 206

ISBN-13:

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The linear discriminant function; Discrete classification models; Error rates and the problem of bias; The variable-selection problem; Special topics; Computer programs.


Discriminant Analysis and Statistical Pattern Recognition

Discriminant Analysis and Statistical Pattern Recognition

Author: Geoffrey J. McLachlan

Publisher: John Wiley & Sons

Published: 2005-02-25

Total Pages: 552

ISBN-13: 0471725285

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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.


Discrete Data Analysis with R

Discrete Data Analysis with R

Author: Michael Friendly

Publisher: CRC Press

Published: 2015-12-16

Total Pages: 700

ISBN-13: 1498725864

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An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth


Statistics for Marketing and Consumer Research

Statistics for Marketing and Consumer Research

Author: Mario Mazzocchi

Publisher: SAGE

Published: 2008-05-22

Total Pages: 433

ISBN-13: 1446204014

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Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied. The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including: - 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots) - 136 multiple choice questions for tests This is augmented by in-depth discussion of topics including: - Sampling - Data management and statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling


Statistical Pattern Recognition

Statistical Pattern Recognition

Author: Andrew R. Webb

Publisher: Newnes

Published: 1999

Total Pages: 476

ISBN-13: 9780340741641

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"This book provides an introduction to statistical pattern recognition theory and techniques. Most of the material presented in this book is concerned with discrimination and classification and has been drawn from a wide range of literature including that of engineering, statistics, computer science and the social sciences. This book is an attempt to provide a concise volume containing descriptions of many of the most useful of today's pattern processing techniques including many of the recent advances in nonparametric approaches to discrimination developed in the statistics literature and elsewhere. The techniques are illustrated with examples of real-world applications studies. Pointers are also provided to the diverse literature base where further details on applications, comparative studies and theoretical developments may be obtained"--Page [xv].


Multivariate Statistics for Wildlife and Ecology Research

Multivariate Statistics for Wildlife and Ecology Research

Author: Kevin McGarigal

Publisher: Springer Science & Business Media

Published: 2013-12-01

Total Pages: 293

ISBN-13: 146121288X

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With its focus on the practical application of the techniques of multivariate statistics, this book shapes the powerful tools of statistics for the specific needs of ecologists and makes statistics more applicable to their course of study. It gives readers a solid conceptual understanding of the role of multivariate statistics in ecological applications and the relationships among various techniques, while avoiding detailed mathematics and the underlying theory. More importantly, the reader will gain insight into the type of research questions best handled by each technique and the important considerations in applying them. Whether used as a textbook for specialised courses or as a supplement to general statistics texts, the book emphasises those techniques that students of ecology and natural resources most need to understand and employ in their research. While targeted for upper-division and graduate students in wildlife biology, forestry, and ecology, and for professional wildlife scientists and natural resource managers, this book will also be valuable to researchers in any of the biological sciences.


Applied Multivariate Statistical Analysis and Related Topics with R

Applied Multivariate Statistical Analysis and Related Topics with R

Author: Lang WU

Publisher: EDP Sciences

Published: 2021-04-27

Total Pages: 238

ISBN-13: 2759826023

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Multivariate analysis is a popular area in statistics and data science. This book provides a good balance between conceptual understanding, key theoretical presentation, and detailed implementation with software R for commonly used multivariate analysis models and methods in practice.


Easy Statistics for Food Science with R

Easy Statistics for Food Science with R

Author: Abbas F.M. Alkarkhi

Publisher: Academic Press

Published: 2018-09-18

Total Pages: 229

ISBN-13: 0128142634

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Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data. - Contains numerous step-by-step tutorials help the reader to learn quickly - Covers the theory and application of the statistical techniques - Shows how to analyze data using R software - Provides R scripts for all examples and figures


Digital Signal Processing and Statistical Classification

Digital Signal Processing and Statistical Classification

Author: George J. Miao

Publisher: Artech House

Published: 2002

Total Pages: 522

ISBN-13: 9781580531351

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This is the first book to introduce and integrate advanced digital signal processing (DSP) and classification together, and the only volume to introduce state-of-the-art transforms including DFT, FFT, DCT, DHT, PCT, CDT, and ODT together for DSP and communication applications. You get step-by-step guidance in discrete-time domain signal processing and frequency domain signal analysis; digital filter design and adaptive filtering; multirate digital processing; and statistical signal classification. It also helps you overcome problems associated with multirate A/D and D/A converters.


Discriminant Analysis

Discriminant Analysis

Author: William R. Klecka

Publisher: SAGE

Published: 1980-08

Total Pages: 76

ISBN-13: 9780803914919

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Background. Deriving the canonical discriminant functions. Interpreting the canonical discriminant functions. Classification procedures. Stepwise inclusion of variables. Concluding remarks.