simCMRData: Simulate capture-mark-reencounter (CMR) migratory movement...

In MigConnectivity: Estimate Migratory Connectivity for Migratory Animals

Simulate capture-mark-reencounter (CMR) migratory movement data

Description

Simulate capture-mark-reencounter (CMR) migratory movement data

Usage

simCMRData(psi, banded, r)

Arguments

psi	Transition probabilities between B origin sites and W target sites. B by W matrix
banded	A vector of the number of released animals from each origin site (including those never reencountered in a target site). Length B
r	A vector (length W) of reencounter probabilities at each target site

Value

simCMRData returns a list with the elements:

reencountered

B by W matrix with numbers reencountered at each target site, by origin site

migrated

B by W matrix with numbers migrated to each target site, by origin site. Assumes survival to arrival is 1

input

List containing the inputs to function

Examples

originNames <- c("A", "B", "C")
nOriginSites <- length(originNames)
targetNames <- as.character(1:4)
nTargetSites <- length(targetNames)

psiTrue <- matrix(c(0.5, 0.25, 0.15, 0.1,
                    0.15, 0.4, 0.25, 0.2,
                    0.1, 0.15, 0.2, 0.55), nOriginSites, nTargetSites,
                  TRUE, list(originNames, targetNames))
psiTrue
rowSums(psiTrue)
banded <- c(3000, 6000, 12000); names(banded) <- originNames
rTrue <- c(0.5, 0.6, 0.4, 0.7) ; names(rTrue) <- targetNames
nSims <- 10
reencountered <- psiCalc <- psiEstMCMC <- psiEstBoot <- vector("list", nSims)

set.seed(9001)
for (i in 1:nSims) {
  dataCMR <- simCMRData(psiTrue, banded, rTrue)
  reencountered[[i]] <- dataCMR$reencountered
  psiCalc[[i]] <- calcTransition(banded = banded, reencountered = reencountered[[i]],
                                 originNames = originNames, targetNames = targetNames)

  psiEstMCMC[[i]] <- estTransition(originNames = originNames, targetNames = targetNames,
                              nSamples = 24000, banded = banded,
                              reencountered = reencountered[[i]],
                              method = "MCMC", verbose = 1)

  psiEstBoot[[i]] <- estTransition(originNames = originNames, targetNames = targetNames,
                              nSamples = 400, # this is set low for demonstration
                              banded = banded,
                              reencountered = reencountered[[i]],
                              method = "bootstrap", verbose = 1)
}
psiErrorBoot <- sapply(psiEstBoot, function(x) x$psi$mean - psiTrue, simplify = "array")
psiErrorMCMC <- sapply(psiEstMCMC, function(x) x$psi$mean - psiTrue, simplify = "array")
psiRhat <- sapply(psiEstMCMC, function(x) max(x$BUGSoutput$summary[,"Rhat"]))
psiConvergence <- psiRhat < 1.1
psiErrorMCMC
(psiBiasMCMC <- apply(psiErrorMCMC, 1:2, mean))
(psiBiasBoot <- apply(psiErrorBoot, 1:2, mean))
(psiMAEMCMC <- apply(psiErrorMCMC, 1:2, function(x) mean(abs(x), na.rm = TRUE)))
(psiMAEBoot <- apply(psiErrorBoot, 1:2, function(x) mean(abs(x), na.rm = TRUE)))
library(coda)
psiListsMCMC <- lapply(psiEstMCMC, function(x) as.mcmc.list((x$BUGSoutput)))
for (i in 1:nSims) {
  if (!psiConvergence[i])
    plot(psiListsMCMC[[i]])
}

MigConnectivity documentation built on May 29, 2024, 8:37 a.m.