# Sample the split proportion - proportion of removed workers in a managed split Sample the split proportion - proportion of removed workers in a managed split - used when `p = NULL` - (see `SimParamBee$splitP`). This is just an example. You can provide your own functions that satisfy your needs! ```r splitPUnif(colony, n = 1, min = 0.2, max = 0.4) splitPColonyStrength(colony, n = 1, nWorkersFull = 100, scale = 1) ``` ## Arguments - `colony`: `Colony-class` - `n`: integer, number of samples - `min`: numeric, lower limit for `splitPUnif` - `max`: numeric, upper limit for `splitPUnif` - `nWorkersFull`: numeric, average number of workers in a full/strong colony for `splitPColonyStrength` (actual number can go beyond this value) - `scale`: numeric, scaling of numbers in `splitPColonyStrength` to avoid to narrow range when colonies have a large number of bees (in that case change `nWorkersFull` too!) ## Returns numeric, split proportion ## Details `splitPUnif` samples from a uniform distribution between values 0.2 and 0.4 irrespective of colony strength. `splitPColonyStrength` samples from a beta distribution with mean `a / (a + b)`, where `a = nWorkers + nWorkersFull` and `b = nWorkers`. This beta sampling mimics larger splits for strong colonies and smaller splits for weak colonies - see examples. This is just an example - adapt to your needs! The `nWorkersFull` default value used in this function is geared towards a situation where we simulate ~100 workers per colony (down-scaled simulation for efficiency). If you simulate more workers, you should change the default accordingly. ## Functions * `splitPColonyStrength()`: Sample the split proportion - the proportion of removed workers in a managed split based on the colony strength ## Examples ```r splitPUnif() splitPUnif() p <- splitPUnif(n = 1000) hist(p, breaks = seq(from = 0, to = 1, by = 0.01), xlim = c(0, 1)) # Example for splitPColonyStrength() founderGenomes <- quickHaplo(nInd = 2, nChr = 1, segSites = 100) SP <- SimParamBee$new(founderGenomes) basePop <- createVirginQueens(founderGenomes) drones <- createDrones(x = basePop[1], nInd = 15) colony <- createColony(x = basePop[2]) colony <- cross(colony, drones = drones) colony <- addWorkers(colony, nInd = 10) nWorkers(colony) # weak colony splitPColonyStrength(colony) splitPColonyStrength(colony) colony <- addWorkers(colony, nInd = 100) nWorkers(colony) # strong colony splitPColonyStrength(colony) splitPColonyStrength(colony) # Logic behind splitPColonyStrength() nWorkersFull <- 100 nWorkers <- 0:200 splitP <- 1 - rbeta( n = length(nWorkers), shape1 = nWorkers + nWorkersFull, shape2 = nWorkers ) plot(splitP ~ nWorkers, ylim = c(0, 1)) abline(v = nWorkersFull) pKeep <- 1 - splitP plot(pKeep ~ nWorkers, ylim = c(0, 1)) abline(v = nWorkersFull) ``` ## See Also `SimParamBee` field `splitP`

splitPFun function