A minimal sampling frame for a Nebraska ice fishing creel survey at Lake
McConaughy. Contains 12 weekend sampling days across January-February 2024.
Ice fishing surveys are a degenerate bus-route design where all access points
are sampled with certainty (p_site = 1.0), so only the period
sampling probability (p_period) is specified.
Format
A data frame with 12 rows and 3 columns:
- date
Survey date (Date class), January-February 2024
- day_type
Day type stratum:
"weekday"or"weekend"- p_period
Numeric period sampling probability in
(0, 1]. The probability that a given period is included in the sample.
See also
example_ice_interviews for matching interview data,
creel_design() for ice survey design construction
Other "Example Datasets":
creel_counts_toy,
creel_interviews_toy,
example_aerial_counts,
example_aerial_glmm_counts,
example_aerial_interviews,
example_calendar,
example_camera_counts,
example_camera_interviews,
example_camera_timestamps,
example_catch,
example_counts,
example_ice_interviews,
example_interviews,
example_lengths,
example_sections_calendar,
example_sections_counts,
example_sections_interviews
Examples
data(example_ice_sampling_frame)
head(example_ice_sampling_frame)
#> date day_type p_period
#> 1 2024-01-06 weekend 0.50
#> 2 2024-01-07 weekend 0.50
#> 3 2024-01-13 weekend 0.50
#> 4 2024-01-14 weekend 0.50
#> 5 2024-01-20 weekend 0.55
#> 6 2024-01-21 weekend 0.55
# Build an ice fishing design with scalar period sampling probability
design <- creel_design(
example_ice_sampling_frame,
date = date,
strata = day_type,
survey_type = "ice",
effort_type = "time_on_ice",
p_period = 0.5
)
print(design)
#>
#> ── Creel Survey Design ─────────────────────────────────────────────────────────
#> Type: "ice"
#> Date column: date
#> Strata: day_type
#> Calendar: 12 days (2024-01-06 to 2024-02-11)
#> day_type: 1 level
#> Counts: "none"
#> Interviews: "none"
#> Sections: "none"
#>
#> ── Ice Fishing Design ──
#>
#> Effort type: time_on_ice
#> p_period (global): 0.5