
Summarise creel survey estimates as a formatted table
Source:R/creel-summaries.R
summary.creel_estimates.Rdsummary.creel_estimates() converts a creel_estimates object into a
creel_summary table with human-readable column names, suitable for
display or export.
Usage
# S3 method for class 'creel_estimates'
summary(object, digits = 4L, ...)Arguments
- object
A
creel_estimatesobject returned byestimate_effort(),estimate_catch_rate(),estimate_harvest_rate(),estimate_total_catch(), orestimate_total_harvest().- digits
Integer number of significant digits for numeric columns (default: 4).
- ...
Additional arguments (currently ignored).
Value
A creel_summary S3 object (a list) with components:
- table
A
data.framewith columns: any grouping variables,Estimate,SE,CI Lower,CI Upper,N.- method
Character string — the estimation method.
- variance_method
Character string — the variance method.
- conf_level
Numeric confidence level (e.g. 0.95).
See also
estimate_effort(), estimate_catch_rate(),
estimate_harvest_rate()
Other "Reporting & Diagnostics":
adjust_nonresponse(),
check_completeness(),
compare_variance(),
flag_outliers(),
season_summary(),
standardize_species(),
summarize_boat_composition(),
summarize_by_angler_type(),
summarize_by_county(),
summarize_by_day_type(),
summarize_by_method(),
summarize_by_species_sought(),
summarize_by_trip_length(),
summarize_by_zip(),
summarize_cws_rates(),
summarize_hws_rates(),
summarize_length_freq(),
summarize_refusals(),
summarize_successful_parties(),
summarize_trips(),
tidy.creel_estimates(),
validate_creel_data(),
validate_design(),
validate_incomplete_trips(),
validation_report(),
write_estimates()
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%)
est <- estimate_effort(design)
summary(est)
#> -- Creel Survey Summary (Total | Taylor linearization | 95%) --
#> Estimate SE CI Lower CI Upper N
#> 372.5 13.18 343.8 401.2 14
as.data.frame(summary(est))
#> Estimate SE CI Lower CI Upper N
#> 1 372.5 13.18 343.8 401.2 14