Supplement 1. 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.
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
Reference: Peres-Neto, P. R., P. Legendre, S. Dray, and D. Borcard. 2006. Partitioning of species data matrices: estimation and comparison of fractions. Ecology 87:2614–2625.