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(RANKIN) of equivocation information (1-:) and interaction information (M). The method is described in the present paper for I: and in a previous paper (Orloci, 1976) for M. The results presented in this paper suggest that for Species Rank order Information Percentage of total* species to be weighted according to their suitability to I· M I M r M characterize isolated groups of releves in a phytosociolo 5 7 54.15 2.31 17.97 0.82 gical table, the equivocation information may serve as a 9 5 49.86 23.19 16.55 8.22 3 3 9 47.79 0.56 15.86 0.20 suitable weight. The appropriate formulations are derived 6 4 8 36.18 1.18 12.01 0.42 4 5 3 24.36 59.34 8.09 21.03 and computed for some data from a salt marsh community. 8 6 4 24.25 39.04 8.05 13.84 10 7 I 21.96 71.17 7.29 25.23 7 8 2 18.67 69.01 6.20 24.46 9 10 18.40 6.11 10 6 5.64 16.31 1.87 5.78 References Total 301.00* 282.11 * 100.00 100.00 Feoli, E. 1973. An index for weighing characters in monothetic classifications. (Italian with English summary). Giorn. Bot. Ita!' 107: 263-268. Gower, J.e. 1967. A comparison of some methods of cluster is a monotone, increasing function of sample size if .. ).
The subject of this book is the incorporation and integration of mathematical and statistical techniques and information science topics into the field of classification, data analysis, and knowledge organization. Readers will find survey papers as well as research papers and reports on newest results. The papers are a combination of theoretical issues and applications in special fields: Spatial Data Analysis, Economics, Medicine, Biology, and Linguistics.
There are many books and computer programs dealing look ahead rather than pondering the past. This is a with data analysis. It would be easy to count at least a manual of recent views that evolved in the study of hundred, yet few of these would show applications in vegetation. This book is intended to emphasize the new vegetation science. Today in the face of environmental acquisitions which we believe significantly affect the degradation caused by anthropogenic pressures on the future of vegetation analysis: biosphere there is added urgency to study vegetation 1. Vegetation is a 'fuzzy' system, it must be treated as processes and dynamics in order to understand their role such at the set level, where the idea ofconceptualized in regulating the water, oxygen and the carbon cycles, in patterns must drive the research design. relation to global warming and ozone layer depletion. It 2. Vegetation cannot be seen only in the perspective of a is well known that ecology was developed first in vegeta traditional taxonomy based on the species concept; tion studies (see Acot 1989) but after an active period character sets of ecological value must enter into marked by intensive phytoclimatic and synecological consideration and a hierarchical analysis of patterns studies, vegetation science entered in a rather dormant and processes should be the basis of comparisons. period. Other ecological disciplines such as animal popu 3.
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization, bootstrapping, and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications, with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression, and Bayesian methods Makes it easy for biologists, researchers, and students to understand the methods used Provides information about computer programs and packages to implement calculations, particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style, with minimal coverage of theoretical details, this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students, as well as a reference for researchers from a range of disciplines. The detailed, worked examples of real applications will enable practitioners to apply the methods to their own biological data.
This book is the outgrowth of the COMETT II Course on Advanced Instru mentation, Data Interpretation, and Control of Biotechnological Processes organized by the Katholieke Universiteit Leuven and the Universiteit Gent, and held at Gent, Belgium, October 1994. The editors of the present volume were very fortunate to find all invited speakers prepared to write state-of-the-art expositions based on their lec tures. Special thanks are due to all of them. The result is an account of recent advances in instrumentation, data interpretation, and model based op timization and control of bioprocesses. For anyone interested in this emerg ing field, this text is of value and provides comprehensive reviews as well as new and important trends and directions for the future, motivated and illustrated by a wealth of applications. The typesetting of all this material represented a tremendous amount of work. I am most grateful to my wife, Myriam Uyttendaele, and to Kurt Gheys, who did most of the proof-reading. Their efforts have increased a lot the uniformity in style and presentation of the different manuscripts. Many thanks also to the co-editors, for their continued support. Kluwer Academic Publishers is gratefully acknowledged for publishing this book, thus contributing to the transfer of the latest research results into large scale industrial applications.