Inicio Inicio

CCAMLR

Comisión para la Conservación de los Recursos Vivos Marinos Antárticos

  • Inicio
  • Contenido
  • Inicio de sesión

Formulario de búsqueda

  • Medidas de conservación
  • Acerca de la CCRVMA
  • Ciencia
  • Circulares
  • Datos
  • Ejecución
  • Publicaciones
  • Reuniones
  • Pesquerías
  • English
  • Français
  • Русский
  • Español
  • Inicio
  • Publications
  • CCAMLR Science
  • CCAMLR Science, Volume 15
  • CCAMLR Science, Volume 15 (2008):115–138

Publicaciones

  • Documentos básicos
  • Folleto de la CCRVMA
  • Informes de pesquerías
  • Archivo de informes de pesquerías
  • Segunda Evaluación del Funcionamiento de la CCRVMA
  • Documentos relacionados con la pesca
  • Manuales y procedimientos
  • Carteles y otros materiales promocionales
  • Resúmenes de documentos de trabajo
  • Medidas de conservación
    • Medidas de conservación vigentes en el pasado y actualmente
    • Pasar revista a las Medidas de Conservación
  • Archivo de referencia sobre artes de pesca
  • Boletín Estadístico
    • Archivo del Boletín Estadístico
  • CCAMLR Science
    • Números publicados de CCAMLR Science
  • Para solicitar publicaciones
    • Informes de las reuniones (2013) – Venta de copias impresas
Print this page
Increase font size
Decrease font size

CCAMLR Science, Volume 15 (2008):115–138

Journal Volume:
CCAMLR Science, Volume 15
Page Numbers:
115–138
Autor(es):
Candy, S.G
download attachmentDescargar (523.26 KB)

Estimation of effective sample size for catch-at-age and catch-at-length data using simulated data from the Dirichlet-multinomial distribution

Abstract / Description: 

The incorporation of ‘effective sample size’ (ESS) in integrated assessments is an approximate but simple way of modelling the distribution of catch-at-age or catch-at-length frequencies using a multinomial likelihood when there is extra-multinomial heterogeneity. Accurate estimation of ESS for catch-frequency data for each fishery and fishing year is important for such assessments, and this issue is studied using simulation. Between-haul heterogeneity within fishing year was simulated using samples from the Dirichlet-multinomial (D-M) distribution, with marginal class probabilities generated using a simple age-structured model incorporating fishing selectivity. Four methods of estimation of effective sample size were compared using this simulation model and its variants. One of the methods is based on the lack-of-fit of predictions of class probabilities using aggregate year-level frequencies. The other three estimators use the haul-level frequencies, including a method based on an approximate profile maximum likelihood estimate (PMLE) of the D-M dispersion parameter. The remaining two estimators based on haul-level frequencies are derived from models for the empirical coefficient of variation (CV) in the proportions, with one being based on an existing CV model used for CCAMLR fisheries while the other is a new method. The methods that use haul-level frequencies gave accurate estimators of an ESS that is appropriate for haul-level heterogeneity with increasing accuracy in the following order: (i) the estimator based on the existing CV model; (ii) that based on the new CV model; and (iii) that based on the PMLE. The year-level method gave very inaccurate estimates of this ESS with relative mean square error two orders of magnitude worse than the best haul-level method.

To account for process error in the calculation of the ESS, the lack of fit of the age-structured model in predicting class/bin by year frequencies is used to obtain a single, across-years, over-dispersion parameter. The ESS is then rescaled by dividing by the over-dispersion parameter, and the model refitted, giving a two-step iterative procedure. The ESS will be over-corrected if there is a systematic component to the lack of fit. A simple generic model of systematic lack-of-fit (SLOF) is presented, and its performance, in terms of providing unbiased estimates of ESS when SLOF is either present or absent, is studied using perturbations of the age-structured model. These perturbations consisted of either systematic or random variation across years in one of the selectivity function parameters and similarly for the mortality rate parameter when combined with systematic or random variation in recruitment. The SLOF model substantially reduced the bias when SLOF was present and is useful when its source is not clear or cannot be rectified by changing the underlying age-structured assessment model.

This page was last modified on 16 Nov 2012

Datos de contacto

Correo electrónico: ccamlr [at] ccamlr [dot] org
Teléfono: +61 3 6210 1111
Facsímil: +61 3 6224 8744
Dirección: 181 Macquarie Street, Hobart, 7000, Tasmania, Australia

 

Enlaces destacados

  • Ofertas de empleo
  • Barcos con licencia para pescar
  • Lista de medidas de conservación vigentes en la temporada 2024/25
  • Logros de la CCRVMA

Recent and Upcoming Meetings

  • WG-SAM-2025
  • WG-ASAM-2025
  • WG-EMM-2025

Footer Links Spanish

  • Inicio de sesión
  • Correo electrónico
  • Grupos de discusión de la CCRVMA
  • Grupos-e de la CCRVMA
  • Asistencia técnica
  • Derechos de autor
  • Descargo de responsabilidad y política de confidencialidad
  • Mapa del sitio
© Copyright - the Commission for the Conservation of Antarctic Marine Living Resources 2025, Todos los derechos están reservado..  |  Volver arriba  |  Sitio creado por Eighty Options