HNC_expand: Estimates the composition of ascensions and treats GSI as...

In delomast/escapeLGD: Escapement Estimation at Lower Granite Dam

Estimates the composition of ascensions and treats GSI as known

Description

Estimates the composition of ascensions and treats GSI as known

Usage

HNC_expand(
  trap,
  stratAssign_comp,
  boots = 2000,
  pbt_var,
  timestep_var,
  physTag_var,
  adclip_var,
  tagRates,
  H_vars,
  HNC_vars,
  W_vars,
  wc_binom,
  method = c("Account", "MLE")
)

Arguments

trap	a tibble with data about the trapped fish
stratAssign_comp	tibble with sWeek, stratum showing what stratum each sWeek corresponds to for composition estimation using the trap data
boots	The number of bootstap iterations to run
pbt_var	The column name of the PBT group variable (tag rates are defined for these groups)
timestep_var	The column name of the timestep variable (corresponds to sWeek in stratAssign_comp)
physTag_var	The column name of a logical variable defining whether or not a sample had a physical tag (e.g. CWT) identifying it as hatchery origin with 100% certainty
adclip_var	The column name of the variable defining ad-fin status (values are "AD" or "AI")
tagRates	A tibble with two columns, the first listing PBT groups and the second giving their tag rates
H_vars	A character vector defining one or two variables to estimate composition of the H group
HNC_vars	A character vector defining one or two variables to estimate composition of the HNC group. If method is "MLE" and two variables are defined, the first must be the pbt_var.
W_vars	A character vector defining one or two variables to estimate composition of the W group
wc_binom	The output of expand_wc_binom_night
method	Either "Account" to use the accounting style estimator or "MLE" to use the maximum likelihood estimator

delomast/escapeLGD documentation built on June 9, 2025, 10:52 p.m.