Sample daily effort observations matching example_calendar. One row per
survey date, suitable for use with add_counts() and estimate_effort().
Format
A data frame with 14 rows and 3 columns:
- date
Survey date (Date class), matching example_calendar dates
- day_type
Day type stratum: "weekday" or "weekend", matching calendar
- effort_hours
Numeric angler-hours observed on the survey date
Details
The effort column holds angler-hours, not raw angler counts.
estimate_effort() expands whichever column it is given to the season
without converting units, so a design built on these data reports
angler-hours. Supplying raw instantaneous counts instead would give a total
in angler-days.
See also
example_calendar for matching calendar data, add_counts() to
attach counts to a design
Other "Example Datasets":
creel_counts_toy,
creel_interviews_toy,
example_aerial_counts,
example_aerial_glmm_counts,
example_aerial_interviews,
example_ages,
example_calendar,
example_camera_counts,
example_camera_interviews,
example_camera_timestamps,
example_catch,
example_ice_interviews,
example_ice_sampling_frame,
example_interviews,
example_lengths,
example_sections_calendar,
example_sections_counts,
example_sections_interviews
Examples
# Load and use with a creel design
data(example_calendar)
data(example_counts)
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
result <- estimate_effort(design)
print(result)
#>
#> ── Creel Survey Estimates ──────────────────────────────────────────────────────
#> Method: Total
#> Variance: Taylor linearization
#> Confidence level: 95%
#> Effort target: sampled_days
#>
#> # A tibble: 1 × 7
#> estimate se se_between se_within ci_lower ci_upper n
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 372. 13.2 13.2 0 344. 401. 14