Description Usage Arguments Details Value Author(s) References See Also Examples

This function is a user-friendly way to compute and test eigenvectors for various definitions of spatial weighting matrices.
It combines calls to the functions `scores.listw`

and `ortho.AIC`

.
It allows to test various definitions of the spatial weighting matrix and return results of `scores.listw`

for the best one.

1 |

`Y` |
A matrix with response variables (univariate or multivariate response). |

`nb` |
An object of the class |

`xy` |
Coordinates of the samples, this argument is optional and
is required only if the argument |

`MEM.autocor` |
A string indicating if all MEM must be returned or only those corresponding to positive or negative autocorrelation. |

`f` |
A function of the distance that can be used as a weighting spatial function. This argument is optional. |

`...` |
Others arguments for the function |

This functions allows to test one binary spatial weighting matrix (if only Y and nb are provided).
It allows also to test a weighting function based on distances (if f is provided) and a weighting function with different values of parameters if other arguments of `f`

are provided.

A list with the following elements:

`all ` |
A data.frame where each row correspond to one spatial weighint matrix tested. It contains value of parameteres tested and corrected AIC and number of orthogonal vectors for the best model. |

`best ` |
A list containing results of scores.listw and ortho.AIC of the best spatial weighting matrix according to corrected AIC. |

Stephane Dray

Dray S., Legendre P. and Peres-Neto P. R. (submitted)
Spatial modeling: a comprehensive framework for principal coordinate
analysis of neighbor matrices (PCNM). *Ecological Modelling*.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
## Not run:
data(oribatid)
# Hellinger transformation
fau <- sqrt(oribatid$fau/outer(apply(oribatid$fau,1,sum),rep(1,ncol(oribatid$fau)),"*"))
# remove gradient effect
faudt <- resid(lm(as.matrix(fau)~as.matrix(oribatid$xy)))
# test a binary spatial weighting matrix
nbtri <- tri2nb(as.matrix(oribatid$xy))
tri.res <- test.W(faudt,nbtri)
maxi <- max(unlist(nbdists(nbtri,as.matrix(oribatid$xy))))
# test a simple spatial weighting function of the distance
f1 <- function(x) {1-(x)/(maxi)}
tri.f1 <- test.W(faudt,nbtri,f=f1,xy=as.matrix(oribatid$xy))
# test a spatial weighting function with various values of parameters
f2 <- function(x,dmax,y) {1-(x^y)/(dmax)^y}
tri.f2 <- test.W(faudt,nbtri, f=f2,y=2:10,dmax=maxi,xy=as.matrix(oribatid$xy))
## End(Not run)
``` |

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