Description Usage Arguments Value Author(s) References Examples

Computes the Moran's I correlogram of a single or multiple variables.

1 | ```
lets.correl(x, y, z, equidistant = FALSE, plot = TRUE)
``` |

`x` |
A single numeric variable in vector format or multiple variables in matrix format (as columns). |

`y` |
A distance matrix of class |

`z` |
The number of distance classes to use in the correlogram. |

`equidistant` |
Logical, if |

`plot` |
Logical, if |

Returns a matrix with the Moran's I Observed value, Confidence Interval (95 and Expected value. Also the p value of the randomization test, the mean distance between classes, and the number of observations. quase tudo

Bruno Vilela, Fabricio Villalobos, Lucas Jardim & Jose Alexandre Diniz-Filho

Sokal, R.R. & Oden, N.L. (1978) Spatial autocorrelation in biology. 1. Methodology. Biological Journal of the Linnean Society, 10, 199-228.

Sokal, R.R. & Oden, N.L. (1978) Spatial autocorrelation in biology. 2. Some biological implications and four applications of evolutionary and ecological interest. Biological Journal of the Linnean Society, 10, 229-249.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
## Not run:
data(PAM)
data(IUCN)
# Spatial autocorrelation in description year (species level)
midpoint <- lets.midpoint(PAM)
distan <- lets.distmat(midpoint[, 2:3])
moran <- lets.correl(IUCN$Description, distan, 12,
equidistant = FALSE,
plot = TRUE)
## End(Not run)
``` |

letsR documentation built on Jan. 24, 2018, 6:36 p.m.

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