I have data from experiments for number of variables as logging, salinity and water use of 150 farmers for 1000 time steps. Farmers' information on land size and distance from water source are available. I want to see that if logging salinity and water use is different considering farmer size and distance from water source as a starting point. I am not sure if cluster analysis will be of any help. I expect to see the graph attached here. Any lead for methods to analyze this type of data set!.
Thanks
Models often have many settings, each of which can take a range of values. Together they form what in mathematics is called a parameter space for the model, whose dimensions are the number of settings, and in which every point is a particular combination of values. Cluster analysis or even nonlinear principal component analysis and contingency table evaluation may be an option.
