Closed MKLau closed 10 years ago
NMDS Plot
Similarity Metric = Mutual Information estimate using a Bayesian Dirichlet prior (a = 0.5)
Minimum stress for given dimensionality: 0.08424578 r^2 for minimum stress configuration: 0.9836413
Source X1 X2 r2 Pr Run 0.99436 0.10602 0.3911 0.001 Prey -0.40429 -0.91463 0.4670 0.001 b -0.97275 0.23184 0.4201 0.001 a -0.97275 0.23184 0.4201 0.001 K -0.30194 0.95333 0.0597 0.005 d -0.44675 0.89466 0.0004 0.969
P values based on 999 permutations.
Implementing the kd-tree based methods of Moniz et al. 2007.
The mi.Dirichlet function depends on a table of counts for a set of values.
NMDS Plot
Similarity Metric = Mutual Information estimate using a Bayesian Dirichlet prior (a = 0.5)
Minimum stress for given dimensionality: 0.08424578 r^2 for minimum stress configuration: 0.9836413
Source X1 X2 r2 Pr Run 0.99436 0.10602 0.3911 0.001 Prey -0.40429 -0.91463 0.4670 0.001 b -0.97275 0.23184 0.4201 0.001 a -0.97275 0.23184 0.4201 0.001 K -0.30194 0.95333 0.0597 0.005 d -0.44675 0.89466 0.0004 0.969
P values based on 999 permutations.