Vegetation Patterns
The Total Differential Value of a big phytosociological data set
diffval: Vegetation Patterns
Interactively explore a tabulation of a phytosociological matrix
Do the vectors represent the same k-partition?
Check the internal assignment of a given classification
Total Differential Value optimization using Gurobi
Total Differential Value optimization using Hill-climbing algorithms
Total Differential Value optimization using a Simulated Annealing (and...
Obtain a partition using a GRASP algorithm
Obtain a partition using a Greedy-type algorithm
Rearrange a phytosociological table, showing differential taxa on top
The Total Differential Value of a phytosociological table
Find, visualize and explore patterns of differential taxa in vegetation data (namely in a phytosociological table), using the Differential Value (DiffVal). Patterns are searched through mathematical optimization algorithms. Ultimately, Total Differential Value (TDV) optimization aims at obtaining classifications of vegetation data based on differential taxa, as in the traditional geobotanical approach (Monteiro-Henriques 2025, <doi:10.3897/VCS.140466>). The Gurobi optimizer, as well as the R package 'gurobi', can be installed from <https://www.gurobi.com/products/gurobi-optimizer/>. The useful vignette Gurobi Installation Guide, from package 'prioritizr', can be found here: <https://prioritizr.net/articles/gurobi_installation_guide.html>.