The Convex hull model predicts that a species is present at sites inside the convex hull of a set of training points, and absent outside that hull. I.e. this is the spatial convex hull, not an environmental hull.

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`p` |
point locations (presence). Two column matrix, data.frame or SpatialPoints* object |

`...` |
Additional arguments. See details |

You can supply an argument n (>= 1) to get n convex hulls around subsets of the points. You can also set n=1:x, to get a set of overlapping polygons consisting of 1 to x parts. I.e. the first polygon has 1 part, the second has 2 parts, and x has x parts.

An object of class 'ConvexHull' (inherits from `DistModel-class`

)

Robert J. Hijmans

`predict, geoDist, maxent, domain, mahal`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
r <- raster(system.file("external/rlogo.grd", package="raster"))
#presence data
pts <- matrix(c(17, 42, 85, 70, 19, 53, 26, 84, 84, 46, 48, 85, 4, 95, 48, 54, 66,
74, 50, 48, 28, 73, 38, 56, 43, 29, 63, 22, 46, 45, 7, 60, 46, 34, 14, 51, 70, 31, 39, 26), ncol=2)
train <- pts[1:12, ]
test <- pts[13:20, ]
ch <- convHull(train)
predict(ch, test)
plot(r)
plot(ch, border='red', lwd=2, add=TRUE)
points(train, col='red', pch=20, cex=2)
points(test, col='black', pch=20, cex=2)
pr <- predict(ch, r, progress='')
plot(pr)
points(test, col='black', pch=20, cex=2)
points(train, col='red', pch=20, cex=2)
# to get the polygons:
p <- polygons(ch)
p
``` |

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