Example interview data for spatially stratified creel survey

Angler interview data for a 3-section lake (North, Central, South) with 9 interviews per section (27 total). Catch rates differ materially across sections: South has approximately 2.5x the catch rate of North, making this dataset suitable for demonstrating spatially stratified estimation. The catch_kept column enables estimate_total_harvest() in addition to estimate_catch_rate() and estimate_total_catch().

Usage

example_sections_interviews

Format

A data frame with 27 rows and 9 columns:

date

Interview date (Date class), matching example_sections_calendar

day_type

Day type stratum: "weekday" or "weekend"

section

Section identifier: "North", "Central", or "South"

catch_total

Integer total fish caught per interview

catch_kept

Integer fish harvested (kept); always <= catch_total

hours_fished

Numeric fishing effort in hours

trip_status

Character trip completion status; "complete" for all 27 interviews

trip_duration

Numeric trip duration in hours

interview_id

Integer interview identifier (1 to 27)

Source

Simulated data for package examples

See also

example_sections_calendar, example_sections_counts, add_interviews(), estimate_catch_rate(), estimate_total_catch()

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_ice_sampling_frame, example_interviews, example_lengths, example_sections_calendar, example_sections_counts

Examples

data(example_sections_calendar)
data(example_sections_counts)
data(example_sections_interviews)

sections_df <- data.frame(
  section = c("North", "Central", "South"),
  stringsAsFactors = FALSE
)
design <- creel_design(example_sections_calendar, date = date, strata = day_type)
design <- add_sections(design, sections_df, section_col = section)
design <- suppressWarnings(add_counts(design, example_sections_counts))
design <- suppressWarnings(add_interviews(design, example_sections_interviews,
  catch = catch_total, effort = hours_fished,
  harvest = catch_kept,
  trip_status = trip_status, trip_duration = trip_duration
))
#> ℹ No `n_anglers` provided — assuming 1 angler per interview.
#> ℹ Pass `n_anglers = <column>` to use actual party sizes for angler-hour
#>   normalization.
#> ℹ Added 27 interviews: 27 complete (100%), 0 incomplete (0%)
estimate_total_catch(design, aggregate_sections = TRUE)
#> 
#> ── Creel Survey Estimates ──────────────────────────────────────────────────────
#> Method: product-total-catch-sections
#> Variance: Taylor linearization
#> Confidence level: 95%
#> Grouped by: section
#> Effort target: sampled_days
#> 
#> # A tibble: 4 × 8
#>   section     estimate    se ci_lower ci_upper     n prop_of_lake_total
#>   <chr>          <dbl> <dbl>    <dbl>    <dbl> <int>              <dbl>
#> 1 North           285.  23.1     240.     331.     9              0.228
#> 2 Central         711.  29.9     653.     770.     9              0.567
#> 3 South           257.  22.7     213.     302.     9              0.205
#> 4 .lake_total    1254.  44.1    1156.    1352.     3              1    
#> # ℹ 1 more variable: data_available <lgl>