GLIM for ecologists

著者

書誌事項

GLIM for ecologists

Michael J. Crawley

（Methods in ecology）

Blackwell Scientific Publications, 1993

  • : pbk

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注記

System requirements for computer disk: IBM-compatible PC; DOS. Source code in ASCII

Bibliography: p. 362-363

Includes index

内容説明・目次

内容説明

GLIM is one of the most powerful and efficient software packages for statistical analysis commercially avialable. The package can handle most of the analysis that ecologists are likely to carry out: regression, analysis of variance; log-linear models of counts, models in which the variance increases with the mean, models of survival, and much more. One of the objectives of statistical analysis is to distil a long and complicated set of data into a small number of meaningful descriptive statistics. The major drawback with the majority of commercially avilable packages is that they generate huge amounts of data output. GLIM, however, only tells the user what it is explicitly asked for. An initial encounter with GLIM can be a daunting experience for the beginner and a clear and comprehensive introduction to the package is essential. GLIM for Ecologists introduces the reader, step-by-step, to the methods of generalised linear modelling using the GLIM statistical language. Every ecologist intending to use the package will benefit from using the book as a guide through the initially impenetrable GLIM language. The book is appropriate for students and professionals alike and assumes that the reader has a working knowledge of linear regression, analysis of variance, significance tests, running programes on a desktop computer, and directory structure and file management in DOS. The book contains a wealth of exercises and examples and all of the data sets used in the book are available on disc.

目次

  • Preface
  • An Ecological Example
  • The GLIM Language
  • Introduction to Experimental Design
  • Understanding Data: Graphical Analysis
  • Understanding Data: Basic Statistics
  • Regression and GLIM
  • Anova and GLIM
  • Analysis of Covariance in GLIM
  • Linear Models
  • Model Simplification
  • Model Criticism
  • Analysing Count Data: Poisson Errors
  • Analysing Proportion Data: Binomial Errors
  • Binary Response Variables
  • Data with Gamma Errors
  • Survival Data
  • Ecological Techniques
  • What GLIM Doesn't Do
  • Programming in GLIM
  • Technical Appendices
  • Statistical Tables
  • Library of GLIM Programmes and Macros (on disk)

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