Generate model predictions for a specific survey date

Calculates the probability P(K | length) that a fish in a given length class is observed with K annuli.

Usage

generate_model_predictions_for_date(
  survey_date,
  G,
  a,
  l,
  mu,
  kappa,
  annuli_date,
  annuli_min_age
)

Arguments

survey_date

Numeric survey date (e.g., 2023.25).

G

Greens function matrix (rows = ages, cols = length classes).

a

Numeric vector of high-resolution ages corresponding to rows of G.

l

Numeric vector of lengths corresponding to columns of G.

mu

Mean spawning date as a fraction of a year in [0, 1).

kappa

Spawning concentration parameter.

annuli_date

Ring formation day as fraction of a year in [0, 1).

annuli_min_age

Minimum age (years) at which the first ring can form.

Value

A matrix of probabilities P(K|l) with rows named by Length and columns by K.

Examples

# Minimal schematic example (using toy inputs)
a <- seq(0, 3, length.out = 5)
l <- seq(10, 30, length.out = 3)
G <- matrix(abs(sin(outer(a, l, "+"))), nrow = length(a))
generate_model_predictions_for_date(2023.5, G, a, l, mu = 0.5, kappa = 3,
                                    annuli_date = 0.25, annuli_min_age = 0.5)
#>       K
#> Length         0          1           2         3
#>     10 0.5281034 0.04898685 0.015036502 0.4078732
#>     20 0.5015673 0.02652226 0.007001495 0.4649090
#>     30 0.4806103 0.01506286 0.017937671 0.4863892