CRR328.pdf (3.72 MB)
Download file

Best practices for the provision of prior information for Bayesian stock assessment

Download (3.72 MB)
posted on 2015-01-01, 00:00 authored by Charis Apostolidis, Guillaume Bal, Rainer Froese, Juho Kopra Sakari Kuikka, Adrian Leach, Polina Levontin, Samu Mäntyniemi, Niall Ó Maoiléidigh, John Mumford, Henni Pulkkinen Etienne Rivot, Atso Romakkaniemi• Vaishav Soni, Konstantinos Stergiou, Jonathan White, Rebecca Whitlock

The manual begins by introducing the basic concepts of Bayesian inference and the role of prior information in the inference. Bayesian analysis is a mathematical formalization of a sequential learning process in a probabilistic rationale. Prior information (also called ”prior knowledge”, ”prior belief”, or simply a ”prior”) refers to any existing relevant knowledge available before the analysis of the newest observations (data) and the information included in them. Prior information is input to a Bayesian statistical analysis in the form of a probability distribution (a prior distribution) that summarizes beliefs about the parameter concerned in terms of relative support for different values. Apart from specifying probable parameter values, prior information also defines how the data are related to the phenomenon being studied, i.e. the model structure. Prior information should reflect the different degrees of knowledge about different parameters and the interrelationships among them.


Published under the auspices of the following ICES Steering Group or Committee


Published under the auspices of the following ICES Expert Group or Strategic Initiative



ICES Cooperative Research Reports (CRR)



Contributors (Editors)

A. Romakkaniemi

Contributors (Authors)

Charis Apostolidis; Guillaume Bal; Rainer Froese; Juho Kopra Sakari Kuikka; Adrian Leach; Polina Levontin; Samu Mäntyniemi; Niall Ó Maoiléidigh; John Mumford; Henni Pulkkinen Etienne Rivot; Atso Romakkaniemi; Vaishav Soni; Konstantinos Stergiou; Jonathan White; Rebecca Whitlock

Series Editor/s

Emory D. Anderson





Recommended citation

A. Romakkaniemi (Ed.). 2015. Best practices for the provision of prior information for Bayesian stock assessment . ICES Cooperative Research Report, Vol. 328. 93 pp.