In very simple terms, a Bayesian analysis involves drawing estimatable parameter values from some prior distribution, computing population dynamics and assigning a likelihood value to each combination based on comparisons to data containing information on population size and/or trend. A posterior distribution may then be constructed and conclusions drawn about the parameter estimates. In Model Ia (see Appendix) r B1 , r B2 , ( ) 1 arg ~ ln B Nt , ( ) 2 arg ~ ln B Nt are the parameter values drawn from priors for the intrinsic growth rate and the log of the recent abundance for the two populations under consideration.
Reference:
Müller, A., & Butterworth, D. S. (2010). Prior incoherence within a Bayesian assessment of the Southern Hemisphere humpback whale breeding stock B population. MARAM IWS/DEC10/MISC/P1
Müller, A., & Butterworth, D. S. (2010). Prior incoherence within a Bayesian assessment of the Southern Hemisphere humpback whale breeding stock B population University of Cape Town ,Faculty of Science ,Marine Resource Assessment and Management Group. Retrieved from http://hdl.handle.net/11427/18912
Müller, Andrea, and Doug S Butterworth Prior incoherence within a Bayesian assessment of the Southern Hemisphere humpback whale breeding stock B population. University of Cape Town ,Faculty of Science ,Marine Resource Assessment and Management Group, 2010. http://hdl.handle.net/11427/18912
Müller A, Butterworth DS. Prior incoherence within a Bayesian assessment of the Southern Hemisphere humpback whale breeding stock B population. 2010 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/18912