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Compute OSA residuals for composition data

get_osa.Rd

Formats observed and expected composition data and calculates one-step-ahead (OSA) residuals using multinomial, Dirichlet-multinomial, or logistic-normal likelihoods. This function is the main interface for residual diagnostics, internally calling [run_osa()] to perform the residual calculations.

Usage

get_osa(
  obs_mat,
  exp_mat,
  N = NULL,
  DM_theta = NULL,
  LN_Sigma = NULL,
  years,
  fleet,
  bins,
  comp_type,
  bin_label,
  comp_like = 0,
  addtocomp = 0
)

Arguments

obs_mat

Array of observed compositions, dimensioned by [region, year, bin, sex, fleet]. May contain NAs, which are removed when filtering by years.

exp_mat

Array of expected compositions, dimensioned the same as obs_mat. May contain NAs, which are removed when filtering by years.

N

Input (or effective if Multinomial) sample size. Dimensions depend on comp_type:

  • comp_type = 0 (aggregated): vector of length n_years.

  • comp_type = 1 (split by region and sex): array [n_regions, n_years, n_sexes].

  • comp_type = 2 (split by region, joint by sex): matrix [n_regions, n_years].

For years without data, users can simply input an NA or any abritary number (it gets filtered out within the function).

DM_theta

Dirichlet-multinomial overdispersion parameter(s). Dimensions must match N:

  • aggregated: scalar

  • split by sex: matrix [n_regions, n_sexes]

  • joint by sex: vector of length n_regions

LN_Sigma

Logistic-normal covariance matrix. Dimensions depend on comp_type:

  • aggregated: matrix [n_bins, n_bins]

  • split by region and sex: array [n_regions, n_bins, n_bins, n_sexes]

  • joint by sex: array [n_regions, n_bins, n_bins]

Use [get_logistN_Sigma()] to help construct this input.

years

Vector of years to filter to if composition type is aggregated (0). Otherwise, this expects a list where each list element is a vector of years for each region where compositions are available for use (split by region and sex, or split by region, joint by sex).

fleet

Fleet identifier (character or numeric) to filter to.

bins

Vector of age or length bin labels corresponding to the composition categories.

comp_type

Integer specifying how compositions are structured:

  • 0 = aggregated across regions and sexes

  • 1 = split by region and sex

  • 2 = split by region, joint by sex

bin_label

Character label describing whether bins represent ages or lengths.

comp_like

Integer specifying the likelihood type (defaults to 0):

  • 0 = multinomial

  • 1 = Dirichlet-multinomial

  • 2–4 = logistic-normal variants

addtocomp

Constant that is added to compositions

Value

A list with one element:

res

Data frame of OSA residuals. Columns include: fleet, index_label, year, index, resid, region, sex, and comp_type.

See also

Other Model Diagnostics: do_jitter(), do_likelihood_profile(), do_retrospective(), do_runs_test(), get_catch_fits_plot(), get_comp_prop(), get_idx_fits(), get_idx_fits_plot(), get_model_rep_from_mcmc(), get_nLL_plot(), get_retrospective_plot(), get_retrospective_relative_difference(), plot_resids()