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Estimate trap rate

mm_traprate_estimate.Rd

Computes the estimated trap rate and uncertainty using bootstrapping, with optional support for stratified estimation based on area-weighted averaging.

Usage

mm_traprate_estimate(data, strata = NULL, n_bootstrap = 1000)

Arguments

data

A data frame as returned by mm_traprate_data() with columns n and effort.

strata

Optional. A data frame defining strata, with columns stratumID and area.

n_bootstrap

Number of bootstrap replicates to estimate uncertainty. Default is 1000.

Value

A data frame with the following columns:

  • estimate: Trap rate estimate (e.g., detections per day)

  • se: Standard error of the estimate

  • cv: Coefficient of variation

  • lower_ci: Lower bound of the 95\

  • upper_ci: Upper bound of the 95\

  • n: Number of deployments or observation used

  • unit: Effort unit

See also

mm_get_effort(), mm_traprate_data()

Examples


data("camtrapdp")
deployments <- camtrapdp$data$deployments
observations <- camtrapdp$data$observations %>%
                  dplyr::filter(scientificName == "Vulpes vulpes")

trap_rate <- mm_traprate_data(observation_data = observations,
                              deployment_data = deployments,
                              use_deployment = FALSE,
                              deployment_column = deploymentID,
                              datetime_column = timestamp,
                              start = start, end = 'end'
)

mm_traprate_estimate(data = trap_rate, n_bootstrap = 1000)
#>            estimate        se        cv  lower_ci upper_ci n   unit
#> trap_rate 0.6206041 0.1829947 0.2948655 0.2985075 1.020408 3 n/days