indicator_moran | R Documentation |
This functions computes the Moran's spatial correlation index (with lag one). It also computes a null value obtained by randomizing the matrix.
indicator_moran(input, subsize = 1, nulln = 99)
input |
An matrix or a list of matrix object. It should be a square matrix |
subsize |
logical. Dimension of the submatrix used to coarse-grain the original matrix (set to 1 for no coarse-graining). |
nulln |
Number of replicates to produce to estimate null distribution of index (default: 999). |
A list (or a list of those if input is a list of matrix object) of:
'value': Spatial autocorrelation of the matrix
If nulln is above 2, then the list has the following additional components :
'null_mean': Mean autocorrelation of the null distribution
'null_sd': SD of autocorrelation in the null distribution
'z_score': Z-score of the observed value in the null distribution
'pval': p-value based on the rank of the observed autocorrelation in the null distribution.
Dakos, V., van Nes, E. H., Donangelo, R., Fort, H., & Scheffer, M. (2010). Spatial correlation as leading indicator of catastrophic shifts. Theoretical Ecology, 3(3), 163-174.
Legendre, P., & Legendre, L. F. J. (2012). Numerical Ecology. Elsevier Science.
## Not run: data(serengeti) # One matrix indicator_moran(serengeti[[1]]) # Several matrices indicator_moran(serengeti) ## End(Not run)
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