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distsampOpen <- function(lambdaformula, gammaformula, omegaformula, pformula,
data, keyfun=c("halfnorm", "exp", "hazard", "uniform"),
output=c("abund", "density"), unitsOut=c("ha", "kmsq"),
mixture=c("P", "NB", "ZIP"), K,
dynamics=c("constant", "autoreg", "notrend", "trend", "ricker", "gompertz"),
fix=c("none", "gamma", "omega"), immigration=FALSE, iotaformula = ~1,
starts, method="BFGS", se=TRUE, ...)
{
#Check data source
if(!is(data, "unmarkedFrameDSO"))
stop("Data is not of class unmarkedFrameDSO.")
#Check detection model arguments
keyfun <- match.arg(keyfun)
if(!keyfun %in% c("halfnorm", "exp", "hazard", "uniform"))
stop("keyfun must be 'halfnorm', 'exp', 'hazard', or 'uniform'")
if(keyfun == "uniform"){
if(!missing(pformula)){
warning("pformula is ignored when using a uniform key function")
}
pformula <- ~1
}
output <- match.arg(output)
unitsOut <- match.arg(unitsOut)
db <- data@dist.breaks
w <- diff(db)
tlength <- data@tlength
survey <- data@survey
unitsIn <- data@unitsIn
#Check state model arguments
mixture <- match.arg(mixture)
dynamics <- match.arg(dynamics)
if((identical(dynamics, "constant") || identical(dynamics, "notrend")) & immigration)
stop("You can not include immigration in the constant or notrend models")
if(identical(dynamics, "notrend") &
!identical(lambdaformula, omegaformula))
stop("lambdaformula and omegaformula must be identical for notrend model")
fix <- match.arg(fix)
formlist <- mget(c("lambdaformula", "gammaformula", "omegaformula",
"pformula", "iotaformula"))
check_no_support(formlist)
formula <- as.formula(paste(unlist(formlist), collapse=" "))
D <- getDesign(data, formula)
y <- D$y
Xlam <- D$Xlam
Xgam <- D$Xgam
Xom <- D$Xom
Xsig <- D$Xp
Xiota<- D$Xiota
delta <- D$delta; go.dims <- D$go.dims
deltamax <- max(delta, na.rm=TRUE)
M <- nrow(y)
T <- data@numPrimary
J <- ncol(getY(data)) / T
Xlam.offset <- D$Xlam.offset
Xgam.offset <- D$Xgam.offset
Xom.offset <- D$Xom.offset
Xsig.offset <- D$Xp.offset
Xiota.offset<- D$Xiota.offset
y <- array(y, c(M, J, T))
yt <- apply(y, c(1,3), function(x) {
if(all(is.na(x)))
return(NA)
else return(sum(x, na.rm=TRUE))
})
ytna <- apply(is.na(y), c(1,3), all)
ytna <- matrix(ytna, nrow=M)
ytna[] <- as.integer(ytna)
first <- apply(!ytna, 1, function(x) min(which(x)))
last <- apply(!ytna, 1, function(x) max(which(x)))
first1 <- which(first==1)[1]
K <- check_K_multinomial(K, K_adjust = 20, D$y, T) # in utils.R
k <- 0:K
lk <- length(k)
#Some k-related indices to avoid repeated calculations in likelihood
lfac.k <- lgamma(k+1)
kmyt <- array(0, c(lk, T, M))
lfac.kmyt <- array(0, c(M, T, lk))
fin <- array(NA, c(M, T, lk)) #Indicator if given k is possible given y
for(i in 1:M) {
for(t in 1:T) {
fin[i,t,] <- k - yt[i,t] >= 0
if(sum(ytna[i,t])==0) {
kmyt[,t,i] <- k - yt[i,t]
lfac.kmyt[i,t, ] <- lgamma(kmyt[,t,i] + 1)
}
}
}
#Transect areas / proportions
ua <- getUA(data) #in utils.R
u <- ua$u; a <- ua$a
if(length(D$removed.sites)>0){
u <- ua$u[-D$removed.sites,]
a <- ua$a[-D$removed.sites,]
}
switch(survey,
line = A <- rowSums(a) * 2,
point = A <- rowSums(a))
switch(unitsIn,
m = A <- A / 1e6,
km = A <- A)
switch(unitsOut,
ha = A <- A * 100,
kmsq = A <- A)
if(output=='abund'){
A <- rep(1, M)
}
lamParms <- colnames(Xlam)
gamParms <- colnames(Xgam)
omParms <- colnames(Xom)
nAP <- ncol(Xlam)
nGP <- ncol(Xgam)
nOP <- ncol(Xom)
#No parameters if uniform key function
nDP <- ifelse(keyfun == "uniform", 0, ncol(Xsig))
detParms <- character(0)
if(keyfun != "uniform") detParms <- colnames(Xsig)
nIP <- ifelse(immigration, ncol(Xiota), 0)
iotaParms <- character(0)
if(immigration) iotaParms <- colnames(Xiota)
if(identical(fix, "gamma")) {
if(!identical(dynamics, "constant"))
stop("dynamics must be constant when fixing gamma or omega")
if(nGP > 1){
stop("gamma covariates not allowed when fix==gamma")
}else {
nGP <- 0
gamParms <- character(0)
}
} else if(identical(dynamics, "notrend")) {
if(nGP > 1){
stop("gamma covariates not allowed when dyamics==notrend")
} else {
nGP <- 0
gamParms <- character(0)
}
}
if(identical(fix, "omega")) {
if(!identical(dynamics, "constant"))
stop("dynamics must be constant when fixing gamma or omega")
if(nOP > 1)
stop("omega covariates not allowed when fix==omega")
else {
nOP <- 0
omParms <- character(0)
}
} else if(identical(dynamics, "trend")) {
if(nOP > 1)
stop("omega covariates not allowed when dynamics='trend'")
else {
nOP <- 0
omParms <- character(0)
}
}
nP <- nAP + nGP + nOP + nDP + nIP + (mixture!="P") + (keyfun == "hazard")
if(!missing(starts) && length(starts) != nP)
stop(paste("The number of starting values should be", nP))
nbParm <- character(0)
if(identical(mixture,"NB"))
nbParm <- "alpha"
else if(identical(mixture, "ZIP"))
nbParm <- "psi"
scaleParm <- character(0)
if(identical(keyfun, "hazard")) scaleParm <- "scale"
paramNames <- c(lamParms, gamParms, omParms, detParms,
iotaParms, scaleParm, nbParm)
#Create indices, all possible combinations of survivors and recruits,
#finding all unique likelihood transitions
I <- cbind(rep(k, times=lk), rep(k, each=lk))
I1 <- I[I[,1] <= I[,2],]
lik_trans <- get_lik_trans(I, I1)
beta_ind <- matrix(NA, 7, 2)
beta_ind[1,] <- c(1, nAP) #Abundance
beta_ind[2,] <- c(1, nGP) + nAP #Gamma
beta_ind[3,] <- c(1, nOP) + nAP + nGP #Omega
beta_ind[4,] <- c(1, nDP) + nAP + nGP + nOP #Sigma
beta_ind[5,] <- c(1, nIP) + nAP + nGP + nOP + nDP #Iota
beta_ind[6,] <- c(1, 1) + nAP + nGP + nOP + nDP + nIP #Hazard scale
beta_ind[7,] <- c(1, 1) + nAP + nGP + nOP + nDP + nIP + (keyfun == "hazard")
#Adjustments to objects to facilitate use in c++
fin <- fin*1 #convert to numeric
u <- t(u) #easier to access column-wise
yperm <- aperm(y, c(1,3,2))
nll <- function(parms) {
nll_distsampOpen(
yperm, yt,
Xlam, Xgam, Xom, Xsig, Xiota,
parms, beta_ind - 1,
Xlam.offset, Xgam.offset, Xom.offset, Xsig.offset, Xiota.offset,
ytna,
lk, mixture, first - 1, last - 1, first1 - 1, M, T,
delta, dynamics, survey, fix, go.dims, immigration,
I, I1, lik_trans$Ib, lik_trans$Ip,
a, u, w, db,
keyfun, lfac.k, kmyt, lfac.kmyt, fin, A
)
}
if(missing(starts)){
starts <- rep(0, nP)
#Need a semi-realistic value for sigma intercept
if(keyfun != "uniform")
starts[beta_ind[4,1]] <- log(mean(w))
}
fm <- optim(starts, nll, method=method, hessian=se, ...)
ests <- fm$par
names(ests) <- paramNames
covMat <- invertHessian(fm, nP, se)
fmAIC <- 2*fm$value + 2*nP
lamEstimates <- unmarkedEstimate(name = "Abundance", short.name = "lam",
estimates = ests[1:nAP], covMat = as.matrix(covMat[1:nAP,1:nAP]),
invlink = "exp", invlinkGrad = "exp")
estimateList <- unmarkedEstimateList(list(lambda=lamEstimates))
gamName <- switch(dynamics, constant = "gamConst", autoreg = "gamAR",
notrend = "", trend = "gamTrend",
ricker="gamRicker", gompertz = "gamGomp")
if(!(identical(fix, "gamma") | identical(dynamics, "notrend"))){
estimateList@estimates$gamma <- unmarkedEstimate(name =
ifelse(identical(dynamics, "constant") | identical(dynamics, "autoreg"),
"Recruitment", "Growth Rate"), short.name = gamName,
estimates = ests[(nAP+1) : (nAP+nGP)], covMat = as.matrix(covMat[(nAP+1) :
(nAP+nGP), (nAP+1) : (nAP+nGP)]),
invlink = "exp", invlinkGrad = "exp")
}
if(!(identical(fix, "omega") | identical(dynamics, "trend"))) {
if(identical(dynamics, "constant") | identical(dynamics, "autoreg") |
identical(dynamics, "notrend")){
estimateList@estimates$omega <- unmarkedEstimate( name="Apparent Survival",
short.name = "omega", estimates = ests[(nAP+nGP+1) :(nAP+nGP+nOP)],
covMat = as.matrix(covMat[(nAP+nGP+1) : (nAP+nGP+nOP),
(nAP+nGP+1) : (nAP+nGP+nOP)]),
invlink = "logistic", invlinkGrad = "logistic.grad")
} else if(identical(dynamics, "ricker")){
estimateList@estimates$omega <- unmarkedEstimate(name="Carrying Capacity",
short.name = "omCarCap", estimates = ests[(nAP+nGP+1) :(nAP+nGP+nOP)],
covMat = as.matrix(covMat[(nAP+nGP+1) : (nAP+nGP+nOP),
(nAP+nGP+1) : (nAP+nGP+nOP)]),
invlink = "exp", invlinkGrad = "exp")
} else{
estimateList@estimates$omega <- unmarkedEstimate(name="Carrying Capacity",
short.name = "omCarCap", estimates = ests[(nAP+nGP+1) :(nAP+nGP+nOP)],
covMat = as.matrix(covMat[(nAP+nGP+1) : (nAP+nGP+nOP),
(nAP+nGP+1) : (nAP+nGP+nOP)]),
invlink = "exp", invlinkGrad = "exp")
}
}
if(keyfun != "uniform"){
estimateList@estimates$det <- unmarkedEstimate(
name = "Detection", short.name = "sigma",
estimates = ests[(nAP+nGP+nOP+1) : (nAP+nGP+nOP+nDP)],
covMat = as.matrix(covMat[(nAP+nGP+nOP+1) : (nAP+nGP+nOP+nDP),
(nAP+nGP+nOP+1) : (nAP+nGP+nOP+nDP)]),
invlink = "exp", invlinkGrad = "exp")
}
if(immigration) {
estimateList@estimates$iota <- unmarkedEstimate(
name="Immigration", short.name = "iota",
estimates = ests[(nAP+nGP+nOP+nDP+1) :(nAP+nGP+nOP+nDP+nIP)],
covMat = as.matrix(covMat[(nAP+nGP+nOP+nDP+1) : (nAP+nGP+nOP+nDP+nIP),
(nAP+nGP+nOP+nDP+1) : (nAP+nGP+nOP+nDP+nIP)]),
invlink = "exp", invlinkGrad = "exp")
}
if(identical(keyfun, "hazard")) {
estimateList@estimates$scale <- unmarkedEstimate(name = "Hazard-rate(scale)",
short.name = "scale", estimates = ests[nAP+nGP+nOP+nDP+nIP+1],
covMat = as.matrix(covMat[nAP+nGP+nOP+nDP+nIP+1,
nAP+nGP+nOP+nDP+nIP+1]),
invlink = "exp", invlinkGrad = "exp")
}
if(identical(mixture, "NB")) {
estimateList@estimates$alpha <- unmarkedEstimate(name = "Dispersion",
short.name = "alpha", estimates = ests[nP],
covMat = as.matrix(covMat[nP, nP]), invlink = "exp",
invlinkGrad = "exp")
}
if(identical(mixture, "ZIP")) {
estimateList@estimates$psi <- unmarkedEstimate(name = "Zero-inflation",
short.name = "psi", estimates = ests[nP],
covMat = as.matrix(covMat[nP, nP]), invlink = "logistic",
invlinkGrad = "logistic.grad")
}
umfit <- new("unmarkedFitDSO", fitType = "distsampOpen",
call = match.call(), formula = formula, formlist = formlist, data = data,
sitesRemoved=D$removed.sites, estimates = estimateList, AIC = fmAIC,
opt = fm, negLogLike = fm$value, nllFun = nll, K = K, mixture = mixture,
dynamics = dynamics, fix = fix, immigration=immigration, keyfun=keyfun,
unitsOut=unitsOut)
return(umfit)
}
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