Input data for Canonical Correspondence Analysis (CCA)

#1
I'm going to conduct Canonical Correspondence Analysis (CCA). In the tutorial I've found at: http://rfunctions.blogspot.com/2016/11/canonical-correspondence-analysis-cca.html environmental data are discrete variables with multiple levels within each variable (please check env.csv file in the tutorial). But in my case some environmental variables belong to nominal and some to ordinal data types with only two levels for each variable. Can I do CCA on my data? Which data types are suitable for CCA? What should I do if my environmental variables would belong to different data types (e.g. continuous, discrete, nominal, etc. with different levels quantity within each variable)?

This question was initially posted at:
https://stats.stackexchange.com/que...ata-for-canonical-correspondence-analysis-cca
 
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