bootstrap: Generate bootstrap estimates of overlap

In ct: Camera Trap Data Management and Multi-Method Ecological Analysis

Generate bootstrap estimates of overlap

Description

The function takes two sets of times of observations and calculates bootstrap estimates of the chosen estimator of overlap. Alternatively, bootstrap estimates can be calculated in a 2-stage process: (1) create a matrix of bootstrap samples for each data set, using ct_resample(); (2) pass these matrices to ct_boot_estimates() to obtain the bootstrap estimates.

A vector of bootstrap estimates can then be used to produce confidence intervals with ct_boot_ci().

Usage

ct_bootstrap(
  A,
  B,
  nb,
  smooth = TRUE,
  kmax = 3,
  adjust = NA,
  n_grid = 128,
  type = c("Dhat1", "Dhat4", "Dhat5"),
  cores = 1
)

ct_resample(x, nb, smooth = TRUE, kmax = 3, adjust = 1, n_grid = 512)

ct_boot_estimates(
  Amat,
  Bmat,
  kmax = 3,
  adjust = c(0.8, 1, 4),
  n_grid = 128,
  type = c("all", "Dhat1", "Dhat4", "Dhat5"),
  cores = 1
)

Arguments

A	A numeric vector of time-of-day observations (in radians, 0 to 2\pi) for species A.
B	A numeric vector of time-of-day observations (in radians, 0 to 2\pi) for species B.
nb	the number of bootstrap samples required
smooth	if TRUE, smoothed bootstrap samples are produced.
kmax	An integer indicating the maximum number of modes allowed in the activity pattern. Default is 3.
adjust	A numeric value to adjust the bandwidth of the kernel density estimation. Default is 1.
n_grid	An integer specifying the number of grid points for density estimation. Default is 128.
type	the name of the estimator to use, or "all" to produce all three estimates. See ct_overlap_estimates() for recommendations on which to use.
cores	the number of cores to use for parallel processing. If NA, all but one of the available cores will used. Parallel processing may take longer than serial processing if the bootstrap runs quickly.
x	a numeric vector of time-of-capture data in radians, ie. on [0, 2\pi] scale
Amat, Bmat	matrices of resampled data for each species produced by resample; see Value below.

Value

The function ct_bootstrap() returns a vector of bootstrap estimates. If estimation fails for a bootstrap sample, the corresponding value will be NA.

The function ct_resample() returns a numeric matrix with each column corresponding to a bootstrap sample. Times are in radians. It may return a matrix of NAs if smooth = TRUE and bandwidth estimation fails.

The Function ct_boot_estimates() with type = "all" returns a numeric matrix with three columns, one for each estimator of overlap, otherwise a vector of bootstrap estimates.

Author(s)

Mike Meredith, Martin Ridout.

References

Ridout & Linkie (2009) Estimating overlap of daily activity patterns from camera trap data. Journal of Agricultural, Biological, and Environmental Statistics 14:322-337

See Also

ct_boot_ci()

Examples

# Generate random data for two species
set.seed(42)
species_A <- runif(100, 1.2, 2 * pi)
species_B <- runif(100, 0.23, 2 * pi)

est <- ct_overlap_estimates(species_A, species_B, type="Dhat4")

boots <- ct_bootstrap(species_A, species_B, 100, type="Dhat4", cores=1)
mean(boots)
hist(boots)
ct_boot_ci(est, boots)

# alternatively:
species_A_gen <- ct_resample(species_A, 100)
species_B_gen <- ct_resample(species_B, 100)
boots <- ct_boot_estimates(species_A_gen, species_B_gen, type="Dhat4", cores=1)
mean(boots)

ct documentation built on Oct. 22, 2026, 1:07 a.m.