Generate starting locations for activity centers

Generate a matrix of initial starting locations, possibly accounting for habitat mask.

initialize_classic(y, M, X, ext, site, hab_mask = FALSE, all_random = FALSE)

Arguments

y

Either a matrix or array of encounter history data, possibly from sim_classic().

M

An integer of the total augmented population size (i.e., detected and augmented individuals). UTMs. An array is used when traps are clustered over a survey area.

X

Either a matrix or array representing the coordinates of traps in UTMs. An array is used when traps are clustered over a survey area.

ext

An Extent object from the raster package. This is returned from grid_classic.

site

Either NULL (if a 2D trap array is used) or a vector of integers denoting which trap array an individual (either detected or augmented) belongs to. Note that site is provided from sim_classic when a 3D trap array is used. However, this site variable must be correctly augmented based on the total augmented population size (i.e., M).

hab_mask

Either FALSE (the default) or a matrix or array output from mask_polygon or mask_raster functions.

all_random

Logical. If TRUE, then encounter data y are ignored and all initial activity center starting locations are randomly chosen. If FALSE (the default), then initial values will be the mean capture location for detected individuals and random locations for augmented individuals.

Value

A matrix of initial activity center coordinates with M rows and 2 columns.

Details

This function generates initial activity center locations based on encounter histories, augmented population size, state-space buffer, and potentially a habitat mask. Note that mean trap detection locations are used for detected individuals while intial values are randomly drawn for augemented individuals. Also, a habitat check will be conducted for all locations when a habitat mask is included.

Author

Daniel Eacker

Examples

# simulate a single trap array with random positional noise
x <- seq(-800, 800, length.out = 5)
y <- seq(-800, 800, length.out = 5)
traps <- as.matrix(expand.grid(x = x, y = y))

# add some random noise to locations
traps <- traps + runif(prod(dim(traps)),-20,20) 

mysigma = 300 # simulate sigma of 300 m
mycrs = 32608 # EPSG for WGS 84 / UTM zone 8N

# Create grid and extent
Grid = grid_classic(X = traps, crs_ = mycrs, buff = 3*mysigma, res = 100)

# simulate SCR data
data3d = sim_classic(X = traps, ext = Grid$ext, crs_ = mycrs, 
sigma_ = mysigma, prop_sex = 1, N = 200, K = 4, base_encounter = 0.25, 
enc_dist = "binomial", hab_mask = FALSE, setSeed = 50)

# generate initial activity center coordinates for 2D trap array without 
# habitat mask
s.st3d = initialize_classic(y=data3d$y, M=500, X=traps, ext = Grid$ext, 
hab_mask = FALSE, all_random = FALSE)

# make simple plot
par(mfrow=c(1,1))
plot(Grid$grid, pch=20,ylab="Northing",xlab="Easting")
points(traps, col="blue",pch=20)
points(s.st3d, col="red",pch=20)