cluster: Detector Clustering

In secr: Spatially Explicit Capture-Recapture

Detector Clustering

Description

Clusters are uniform groups of detectors. Use these functions to extract or replace cluster information of a traps object, or extract cluster information for each detection in a capthist object.

Usage

clusterID(object)
clusterID(object) <- value
clustertrap(object)
clustertrap(object) <- value

Arguments

object	traps or capthist object
value	factor (clusterID) or integer-valued vector (clustertrap)

Details

Easy access to attributes used to define compound designs, those in which a detector array comprises several similar subunits (‘clusters’). ‘clusterID’ identifies the detectors belonging to each cluster, and ‘clustertrap’ is a numeric index used to relate matching detectors in different clusters.

For replacement (‘traps’ only), the number of rows of value must match exactly the number of detectors in object.

‘clusterID’ and ‘clustertrap’ are assigned automatically by trap.builder.

Value

Factor (clusterID) or integer-valued vector (clustertrap).

clusterID(object) may be NULL.

See Also

traps, trap.builder, mash, derivedCluster, cluster.counts, cluster.centres

Examples

## 25 4-detector clusters
mini <- make.grid(nx = 2, ny = 2)
tempgrid <- trap.builder (cluster = mini , method = "all",
    frame = expand.grid(x = seq(100, 500, 100), y = seq(100,
    500, 100)))
clusterID(tempgrid)
clustertrap(tempgrid)

tempCH <- sim.capthist(tempgrid)
table(clusterID(tempCH)) ## detections per cluster
cluster.counts(tempCH)   ## distinct individuals

secr documentation built on April 4, 2025, 2:06 a.m.