like_comp: Likelihood for composition vectors

In multiSA: Multi-Stock Assessment

Likelihood for composition vectors

Description

Returns the log-likelihood for composition data, e.g., length, age, or stock composition, with various statistical distributions supported.

Usage

like_comp(
  obs,
  pred,
  type = c("multinomial", "dirmult1", "dirmult2", "lognormal"),
  N = sum(obs),
  theta,
  stdev
)

Arguments

obs	A vector of observed values. Internally converted to proportions.
pred	A vector of predicted values. Same length as obs. Internally converted to proportions.
type	Character for the desired distribution
N	Numeric, the sample size corresponding to obs for multinomial or Dirichlet multinomial distributions.
theta	Numeric, the linear (type = "dirmult1") or saturating (type = "dirmult2") Dirichlet-multinomial parameter, respectively. See Thorson et al. (2017)
stdev	Numeric or vectorized for obs, the likelihood standard deviation for lognormal distribution.

Details

Observed and predicted vectors are internally converted to proportions.

For type = "lognormal", zero observations are removed from the likelihood calculation.

Value

Numeric representing the log-likelihood.

References

Thorson et al. 2017. Model-based estimates of effective sample size in stock assessment models using the Dirichlet-multinomial distribution. Fish. Res. 192:84-93. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.fishres.2016.06.005")}

Examples

M <- 0.1
age <- seq(1:10)
pred <- exp(-M * age)
obs <- pred * rlnorm(10, sd = 0.05)
like_comp(obs, pred, N = 10, type = "multinomial")
like_comp(obs, pred, N = 100, type = "multinomial")
like_comp(obs, pred, N = 10, type = "dirmult1", theta = 1)
like_comp(obs, pred, N = 10, type = "dirmult1", theta = 20)

multiSA documentation built on March 21, 2026, 1:06 a.m.