stratRejectionSampler_normal: Stratified rejection sampler for multivariate normal point...

In nimbleSCR: Spatial Capture-Recapture (SCR) Methods Using 'nimble'

Stratified rejection sampler for multivariate normal point process

Description

Simulate data using a stratified rejection sampler from a point process with an isotropic multivariate normal decay kernel.

Usage

stratRejectionSampler_normal(
  numPoints,
  lowerCoords,
  upperCoords,
  s,
  windowIntensities,
  sd
)

Arguments

numPoints	Number of spatial points to generate.
lowerCoords, upperCoords	Matrices of lower and upper x- and y-coordinates of a set of detection windows. One row for each window.
s	Vector of x- and y-coordinates of of the isotropic multivariate normal distribution mean.
windowIntensities	Vector of integrated intensities over all detection windows.
sd	Standard deviation of the isotropic multivariate normal distribution.

Value

A matrix of x- and y-coordinates of the generated points. One row corresponds to one point.

Author(s)

Joseph D. Chipperfield and Wei Zhang

Examples

numPoints <- 10
lowerObsCoords <- matrix(c(0, 0, 1, 0, 0, 1, 1, 1), nrow = 4, byrow = TRUE)
upperObsCoords <- matrix(c(1, 1, 2, 1, 1, 2, 2, 2), nrow = 4, byrow = TRUE)
s <- c(1, 1)
windowIntensities <- c(1:4)
sd <- 0.1
set.seed(0)
stratRejectionSampler_normal(numPoints, lowerObsCoords, upperObsCoords, s, windowIntensities, sd)

nimbleSCR documentation built on Dec. 1, 2022, 1:17 a.m.