Michael Greenacre. 2013. Fuzzy coding in constrained ordinations. Ecology 94:280–286. http://dx.doi.org/10.1890/12-0981.1
Supplement
Artificial and real data sets, and R functions and scripts to perform canonical correspondence analysis using fuzzy-coded explanatory variables, with adjustment of the variance explained.
Ecological Archives E094-021-S1.
Authors
File list (downloads)
Description
Michael Greenacre
Department of Economics and Business
Universitat Pompeu Fabra
Ramon Trias Fargas 25--27
Barcelona
E-08005 Spain
Faculty of Biological Sciences, Fisheries and Economics
University of Tromsø
Tromsø
N-9037 Norway
E-mails: michael.greenacre@upf.edu, michael.greenacre@gmail.com
File list
artificial.csv (md5: 2dcf93451985a5205c88df0f24dcc709) - abundance data for 300 samples on 5 species (A, B, C, D and E) and environmental data on 2 variables (X and Y).
BarentsFish.csv (md5: e61ef26ef9a7fec70f831535587a5966) - fish abundance data set ‘BarentsFish’, on 89 samples from the Barents Sea, along with longitude and latitude positions, depth and temperature
fuzzy.tri.R (md5: 0bf5013ae24752cd27ed48e585a53870) - R function fuzzy.tri for fuzzy coding into any number of categories using triangular membership functions
CCA.R (md5: c6b9a3207e7e3405545a673b5a536daa) - R function CCA for basic computations of a CCA
fuzzyscript.R (md5: 4ce442235d7d6e107ff498fc62cc1789) - R script illustrating several analyses from this report (see description below)
Description
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