dbernppLocalACmovement_exp | R Documentation |
Density and random generation functions of the Bernoulli point process for activity center movement between occasions based on a bivariate exponential distribution and local evaluation.
dbernppLocalACmovement_exp( x, lowerCoords, upperCoords, s, lambda = -999, rate, baseIntensities, habitatGrid, habitatGridLocal, resizeFactor = 1, localHabWindowIndices, numLocalHabWindows, numGridRows, numGridCols, numWindows, log = 0 ) rbernppLocalACmovement_exp( n, lowerCoords, upperCoords, s, lambda = -999, rate, baseIntensities, habitatGrid, habitatGridLocal, resizeFactor = 1, localHabWindowIndices, numLocalHabWindows, numGridRows, numGridCols, numWindows )
x |
Vector of x- and y-coordinates of a single spatial point (typically AC location at time t+1) scaled to the habitat (see ( |
lowerCoords, upperCoords |
Matrices of lower and upper x- and y-coordinates of all habitat windows. One row for each window. Each window should be of size 1x1 (after rescaling if necessary). |
s |
Vector of x- and y-coordinates of the isotropic multivariate exponential distribution mean (AC location at time t). |
lambda |
Rate parameter of the isotropic bivariate exponential distribution. Soon deprecated, use argument "rate" instead. |
rate |
Rate parameter of the isotropic bivariate exponential distribution. |
baseIntensities |
Vector of baseline habitat intensities for all habitat windows. |
habitatGrid |
Matrix of habitat window indices. Cell values should correspond to the order of habitat windows in |
habitatGridLocal |
Matrix of rescaled habitat grid cells indices, as returned by the |
resizeFactor |
Aggregation factor used in the |
localHabWindowIndices |
Matrix of indices of local habitat windows around each local habitat grid cell ( |
numLocalHabWindows |
Vector of numbers of local habitat windows around all habitat grid cells, from |
numGridRows, numGridCols |
Numbers of rows and columns of the |
numWindows |
Number of habitat windows. This value (positive integer) is used to truncate |
log |
Logical argument, specifying whether to return the log-probability of the distribution. |
n |
Integer specifying the number of realisations to generate. Only n = 1 is supported. |
The dbernppLocalACmovement_exp
distribution is a NIMBLE custom distribution which can be used to model and simulate
movement of activity centers between consecutive occasions in open population models.
The distribution assumes that the new individual activity center location (x)
follows an isotropic exponential normal centered on the previous activity center (s) with rate (lambda).
The local evaluation approach is implemented.
The (log) probability density of the observation vector x
.
Wei Zhang and Cyril Milleret
W. Zhang, J. D. Chipperfield, J. B. Illian, P. Dupont, C. Milleret, P. de Valpine and R. Bischof. 2020. A hierarchical point process model for spatial capture-recapture data. bioRxiv. DOI 10.1101/2020.10.06.325035
C. Milleret, P. Dupont, C. Bonenfant, H. Broseth, O. Flagstad, C. Sutherland and R. Bischof. 2019. A local evaluation of the individual state-space to scale up Bayesian spatial capture-recapture. Ecology and Evolution 9:352-363
# Creat habitat grid habitatGrid <- matrix(c(1:(4^2)), nrow = 4, ncol=4, byrow = TRUE) coordsHabitatGridCenter <- matrix(c(0.5, 3.5, 1.5, 3.5, 2.5, 3.5, 3.5, 3.5, 0.5, 2.5, 1.5, 2.5, 2.5, 2.5, 3.5, 2.5, 0.5, 1.5, 1.5, 1.5, 2.5, 1.5, 3.5, 1.5, 0.5, 0.5, 1.5, 0.5, 2.5, 0.5, 3.5, 0.5), ncol = 2,byrow = TRUE) colnames(coordsHabitatGridCenter) <- c("x","y") # Create habitat windows lowerCoords <- coordsHabitatGridCenter-0.5 upperCoords <- coordsHabitatGridCenter+0.5 colnames(lowerCoords) <- colnames(upperCoords) <- c("x","y") # Plot check plot(lowerCoords[,"y"]~lowerCoords[,"x"],pch=16, xlim=c(0,4), ylim=c(0,4),col="red") points(upperCoords[,"y"]~upperCoords[,"x"],col="red",pch=16) points(coordsHabitatGridCenter[,"y"]~coordsHabitatGridCenter[,"x"],pch=16) # Rescale coordinates ScaledLowerCoords <- scaleCoordsToHabitatGrid(coordsData = lowerCoords, coordsHabitatGridCenter = coordsHabitatGridCenter) ScaledUpperCoords <- scaleCoordsToHabitatGrid(coordsData = upperCoords, coordsHabitatGridCenter = coordsHabitatGridCenter) ScaledUpperCoords$coordsDataScaled[,2] <- ScaledUpperCoords$coordsDataScaled[,2] + 1 ScaledLowerCoords$coordsDataScaled[,2] <- ScaledLowerCoords$coordsDataScaled[,2] - 1 habitatMask <- matrix(1, nrow = 4, ncol=4, byrow = TRUE) # Create local objects HabWindowsLocal <- getLocalObjects(habitatMask = habitatMask, coords = coordsHabitatGridCenter, dmax=4, resizeFactor = 1, plot.check = TRUE ) s <- c(1, 1) # Currrent activity center location rate <- 0.1 numWindows <- nrow(coordsHabitatGridCenter) baseIntensities <- rep(1,numWindows) numRows <- nrow(habitatGrid) numCols <- ncol(habitatGrid) # The log probability density of moving from (1,1) to (1.2, 0.8) dbernppLocalACmovement_exp(x = c(1.2, 0.8), lowerCoords =lowerCoords, upperCoords = upperCoords, s =s, rate = rate, baseIntensities = baseIntensities, habitatGrid = habitatGrid, habitatGridLocal = HabWindowsLocal$habitatGrid, resizeFactor = HabWindowsLocal$resizeFactor, localHabWindowIndices = HabWindowsLocal$localIndices, numLocalHabWindows = HabWindowsLocal$numLocalIndices, numGridRows = numRows, numGridCols = numCols, numWindows = numWindows, log = TRUE)
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