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)
``` |

spatialwarnings documentation built on Jan. 27, 2018, 3:01 a.m.

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