## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----data-setup---------------------------------------------------------------
library(tidycreel)

data(example_calendar)
data(example_counts)
data(example_interviews)

head(example_calendar)
head(example_counts)
head(example_interviews)

## ----raw-design---------------------------------------------------------------
library(survey)

# Stratum sizes: total days per day_type in the calendar
stratum_sizes <- table(example_calendar$day_type)
stratum_sizes

# Attach FPC to the count frame
counts_frame <- example_counts
counts_frame$fpc <- as.integer(stratum_sizes[counts_frame$day_type])
counts_frame

# Build the stratified survey design
svy_counts <- svydesign(
  ids    = ~1,
  strata = ~day_type,
  fpc    = ~fpc,
  data   = counts_frame
)
svy_counts

## ----raw-effort---------------------------------------------------------------
effort_total <- svytotal(~effort_hours, svy_counts)
effort_total
confint(effort_total)

## ----raw-cpue-----------------------------------------------------------------
# Use complete trips only (standard practice)
complete_trips <- subset(example_interviews, trip_status == "complete")
nrow(complete_trips)

# Build a simple survey design over the interview frame
svy_interviews <- svydesign(ids = ~1, data = complete_trips)

# Ratio estimator: total catch / total effort (ratio-of-means CPUE)
cpue_ratio <- svyratio(~catch_total, ~hours_fished, svy_interviews)
cpue_ratio

## ----raw-total-catch----------------------------------------------------------
effort_coef <- coef(effort_total)[[1]]
cpue_coef <- coef(cpue_ratio)[[1]]
var_effort <- vcov(effort_total)[[1]]
var_cpue <- vcov(cpue_ratio)[[1]]

# Delta method: Var(effort * cpue) = effort^2 * Var(cpue) + cpue^2 * Var(effort)
total_catch_est <- effort_coef * cpue_coef
total_catch_var <- effort_coef^2 * var_cpue + cpue_coef^2 * var_effort
total_catch_se <- sqrt(total_catch_var)

cat("Total catch estimate:", round(total_catch_est, 1), "\n")
cat("Standard error:      ", round(total_catch_se, 1), "\n")
cat(
  "95% CI: [",
  round(total_catch_est - 1.96 * total_catch_se, 1), ",",
  round(total_catch_est + 1.96 * total_catch_se, 1), "]\n"
)

## ----tc-design----------------------------------------------------------------
design <- creel_design(example_calendar, date = date, strata = day_type)
design <- add_counts(design, example_counts)
design

## ----tc-effort----------------------------------------------------------------
effort_est <- estimate_effort(design)
effort_est

## ----tc-interviews------------------------------------------------------------
design <- add_interviews(design, example_interviews,
  catch         = catch_total,
  effort        = hours_fished,
  n_anglers     = n_anglers,
  harvest       = catch_kept,
  trip_status   = trip_status,
  trip_duration = trip_duration
)

## ----tc-cpue------------------------------------------------------------------
cpue_est <- estimate_catch_rate(design)
cpue_est

## ----tc-total-catch-----------------------------------------------------------
total_catch <- estimate_total_catch(design)
total_catch

## ----extract-design, eval = FALSE---------------------------------------------
# # Extract the internal svydesign object for advanced use
# internal_svy <- as_creel_svydesign(design)
# # Now use any survey package function directly
# svymean(~effort_hours, internal_svy)