smartsurv.weight: Evaluate nodes for value in invasion detection (based on a...

In GarrettLab/SeaMonster2: Test

Description

Uses weights that indicate how likely each node was to be the starting location (introduction point) for an invasion. Uses output from smartsurv. Finds the rate at which sampling success (other nodes free of invasion when invasion reaches sampling node) is expected to occur for each potential sampling node.

Usage

smartsurv.weight(ss.out, adjmat, wtvec, nodenam = NA)

Arguments

ss.out	output object from function smartsurv
adjmat	adjacency matrix for evaluation
wtvec	vector of weights indicating the probability that each node would be the starting node for invasion
nodenam	vector of node names

Examples

Amat <- matrix(c(1,0,0,0,1,1,0,0,0,1,1,0,1,1,1,1),nrow=4,ncol=4)
smartsurv(adjmat=Amat, stoch=F, nrealz=1)
sAmat <- Amat * 0.7
ss.outex <- smartsurv(adjmat=sAmat, stoch=T, nrealz=10)
wtvec.ex <- c(1,10,100,1)
smartsurv.weight(ss.out=ss.outex, adjmat=sAmat, wtvec=wtvec.ex)
smartsurv.weight(ss.out=ss.outex, adjmat=sAmat, wtvec=wtvec.ex, nodenam=c("KS","NE","ND","SD"))
smartsurv.weight(ss.out=ss.outex, adjmat=sAmat, wtvec=c(1,100,10,1), nodenam=c("KS","NE","ND","SD"))

GarrettLab/SeaMonster2 documentation built on Dec. 17, 2021, 9:27 p.m.