adegenet (version 1.2-3)

chooseCN: Function to choose a connection network

Description

The function chooseCN is a simple interface to build a connection network (CN) from xy coordinates. The user chooses from 6 types of graph and one additional weighting scheme. chooseCN calls functions from appropriate packages, handles non-unique coordinates and returns a connection network either with classe nb or listw.

Usage

chooseCN(xy, ask = TRUE, type = NULL, result.type = "nb", d1 = NULL, 
    d2 = NULL, k = NULL,  a=NULL, dmin=NULL, plot.nb = TRUE, edit.nb = FALSE)

Arguments

xy

an matrix or data.frame with two columns for x and y coordinates.

ask

a logical stating whether graph should be chosen interactively (TRUE,default) or not (FALSE). Set to FALSE if type is provided.

type

an integer giving the type of graph (see details).

result.type

a character giving the class of the returned object. Either "nb" (default) or "listw", both from spdep package. See details.

d1

the minimum distance between any two neighbours. Used if type=5.

d2

the maximum distance between any two neighbours. Used if type=5. Can also be a character: "dmin" for the minimum distance so that each site has at least one connection, or "dmax" to have all sites connected (despite the later has no

k

the number of neighbours per point. Used if type=6.

a

the exponent of the inverse distance matrix. Used if type=7.

dmin

the minimum distance between any two distinct points. Used to avoid infinite spatial proximities (defined as the inversed spatial distances). Used if type=7.

plot.nb

a logical stating whether the resulting graph should be plotted (TRUE, default) or not (FALSE).

edit.nb

a logical stating whether the resulting graph should be edited manually for corrections (TRUE) or not (FALSE, default).

Value

• Returns a connection network having the class nb or listw. The xy coordinates are passed as attribute to the created object.

encoding

UTF-8

Details

There are 7 kinds of graphs proposed: Delaunay triangulation (type 1) Gabriel graph (type 2) Relative neighbours (type 3) Minimum spanning tree (type 4) Neighbourhood by distance (type 5) K nearests neighbours (type 6) Inverse distances (type 7) The last option (type=7) is not a true neighbouring graph: all sites are neighbours, but the spatial weights are directly proportional to the inversed spatial distances. Also not that in this case, the output of the function is always a listw object, even if nb was requested.

See Also

spca

Examples

data(nancycats)
if(require(spdep) & require(ade4)){

par(mfrow=c(2,2))
cn1 <- chooseCN(nancycats@other$xy,ask=FALSE,type=1)
cn2 <- chooseCN(nancycats@other$xy,ask=FALSE,type=2)
cn3 <- chooseCN(nancycats@other$xy,ask=FALSE,type=3)
cn4 <- chooseCN(nancycats@other$xy,ask=FALSE,type=4)
par(mfrow=c(1,1))
}