ct_fit_rem: Fit Random Encounter Model (REM)

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

Fit Random Encounter Model (REM)

Description

Fits a random encounter model using observed data and trap rate information. Automatically estimates detection radius, detection angle, animal speed, and activity pattern models if not provided.

Usage

ct_fit_rem(
  data,
  traprate_data,
  radius_model = NULL,
  angle_model = NULL,
  speed_model = NULL,
  activity_model = NULL,
  strata = NULL,
  time_of_day,
  n_bootstrap = 1000
)

Arguments

data	A data frame of observations, including distance, angle, speed, and time-of-day (in radians).
traprate_data	A data frame created by ct_traprate_data().
radius_model	Optional. A detection function model for radius (distance) fitted using ct_fit_detmodel().
angle_model	Optional. A detection function model for angle fitted using ct_fit_detmodel().
speed_model	Optional. A model for movement speed fitted using ct_fit_speedmodel().
activity_model	Optional. An activity model fitted with activity::fitact().
strata	Optional. A data frame of stratification information with columns stratumID and area.
time_of_day	The column name (unquoted or as a string) representing time-of-day in radians.
n_bootstrap	Number of bootstrap replicates for uncertainty estimation. Default is 1000.

Value

A data frame with columns:

• parameters: Model parameter name

• estimate: Estimated value

• se: Standard error

• cv: Coefficient of variation

• lower_ci: Lower bound of 95% confidence interval

• upper_ci: Upper bound of 95% confidence interval

See Also

ct_fit_speedmodel(), ct_fit_detmodel(), ct_fit_activity()

Examples

data("ctdp")
deployments <- ctdp$data$deployments
observations <- ctdp$data$observations %>%
  dplyr::filter(scientificName == "Vulpes vulpes") %>%
  # Add time of day
  dplyr::mutate(time_of_day = ct_to_radian(times = timestamp))

# Prepare trap rate data
trap_rate <- ct_traprate_data(observation_data = observations,
                              deployment_data = deployments,
                              deployment_column = deploymentID,
                              datetime_column = timestamp,
                              start = start, end = 'end'
)


# Fit REM
ct_fit_rem(data = observations,
           traprate_data = trap_rate,
           time_of_day = time_of_day)

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