sim_vb_data {lhmixr}

Simulate sex-specific von Bertalanffy data with missing classifications.

Description

sim_vb_data simulates sex-specific growth data according to the von Bertalanffy growth model and a logistic model governing maturity.

Usage

sim_vb_data(nfemale, nmale, mean_ageF, mean_ageM, growth_parF, growth_parM,
  mat_parF, mat_parM, distribution)

Arguments

nfemale

Numeric scalar for number of female observations.

nmale

Numeric scalar for number of male observations.

mean_ageF

Numeric scalar for female mean age - used to generate ages from rnbinom(, mu = mean_ageF)

mean_ageM

Numeric scalar for male mean age - used to generate ages from rnbinom(, mu = mean_ageM)

growth_parF

Named ("linf", "k", "t0", "sigma") numeric vector with female growth parameters

growth_parM

Named ("linf", "k", "t0", "sigma") numeric vector with male growth parameters

mat_parF

Named ("A50", "MR") numeric vector with female maturation parameters A50 is the age at 50% maturity, MR is age range between 25% and 75% mature.

mat_parM

Named ("A50", "MR") numeric vector with male maturation parameters.

distribution

Character with options: "normal" or "lognormal" for simulated length-at-age distributon.

Value

data.frame with columns "age", "length", "true.sex", "obs.sex" (observed sex assuming immature animals are unclassified), "maturity" (binary: 1 if mature; 0 if immature).

Examples

sim.dat <- sim_vb_data(nfemale = 30, nmale = 30, mean_ageF = 3, mean_ageM = 3,
                       growth_parF = c(linf = 30, k = 0.2, t0 = -1, sigma = 0.1),
                       growth_parM = c(linf = 25, k = 0.2, t0 = -1, sigma = 0.1),
                       mat_parF = c(A50 = 3, MR = 1), mat_parM = c(A50 = 2, MR = 1),
                       distribution = "lognormal")

plot(jitter(sim.dat$age), sim.dat$length,
     xlim=c(0, max(sim.dat$age)), ylim = c(0, max(sim.dat$length)),
     col = c("red", "blue", "grey")[match(sim.dat$obs.sex, c("female", "male", "unclassified"))],
     pch = 19, xlab = "age", ylab = "Length")