Description Usage Arguments Value References Examples
View source: R/indicator_moran.R
This functions computes the Moran's spatial correlation index (with lag one). It also computes a null value obtained by randomizing the matrix.
1 | indicator_moran(input, subsize = 1, nreplicates = 999)
|
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). |
nreplicates |
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 nreplicates 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.
1 2 3 4 5 6 7 8 9 10 | ## Not run:
data(serengeti)
# One matrix
indicator_moran(serengeti[1])
# Several matrices
indicator_moran(serengeti)
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.