Compute effort density as effort per acre

Divides all effort estimate columns in a pre-computed creel_estimates object by a surface area scalar (acres). Standard error propagates linearly because acres is a constant (not a random variable), so no Delta Method is needed: se_per_acre = se_effort / acres.

acres is a constant divisor, so the result is whatever the effort was, per acre: the returned unit field composes the effort's own unit ("angler-hours/acre", "party-hours/acre"), and stays NA when the effort's unit was unknown.

This is a composable estimator: the effort object must be pre-computed via estimate_effort before calling this function.

Usage

estimate_effort_per_acre(effort, acres, ...)

Arguments

effort

A creel_estimates object returned by estimate_effort. Must contain estimate, se, ci_lower, and ci_upper columns in effort$estimates.

acres

A single positive numeric scalar giving the total lake surface area in acres. All effort estimate columns are divided by this value.

...

Reserved for future arguments.

Value

A creel_estimates object with method = "effort-per-acre". The estimates tibble has the same rows as the input but with estimate, se, ci_lower, ci_upper (and se_between, se_within when present in the input) all divided by acres. Grouping columns (by_vars) and n are carried through unchanged. variance_method and conf_level are inherited from the input effort object.

See also

estimate_effort, estimate_angler_trips

Examples

data(example_calendar)
data(example_counts)
data(example_interviews)
design <- creel_design(example_calendar, date = date, strata = day_type)
design <- add_counts(design, example_counts)
#> Warning: No weights or probabilities supplied, assuming equal probability
design <- add_interviews(design, example_interviews,
  catch = catch_total, effort = hours_fished, harvest = catch_kept,
  trip_status = trip_status
)
#> Warning: ! No `n_anglers` provided — assuming 1 angler per interview.
#> ℹ Pass `n_anglers = <column>` to use actual party sizes for angler-hour
#>   normalization.
#> ℹ If the interviews really are one angler each, pass `n_anglers = 1` to state
#>   that and silence this warning.
#> ℹ Added 22 interviews: 17 complete (77%), 5 incomplete (23%)
effort <- estimate_effort(design)
# Surface area of the water body, in acres.
estimate_effort_per_acre(effort, acres = 120)
#> 
#> ── Creel Survey Estimates ──────────────────────────────────────────────────────
#> Method: effort-per-acre
#> Variance: Taylor linearization
#> Confidence level: 95%
#> 
#> # A tibble: 1 × 7
#>   estimate    se se_between se_within ci_lower ci_upper     n
#>      <dbl> <dbl>      <dbl>     <dbl>    <dbl>    <dbl> <int>
#> 1     3.10 0.110      0.110         0     2.86     3.34    14