TY - RPRT

T1 - Individual based population inference using tagging data

A1 - Pedersen,Martin Wæver

A1 - Thygesen,Uffe Høgsbro

A1 - Baktoft,Henrik

A1 - Madsen,Henrik

AU - Pedersen,Martin Wæver

AU - Thygesen,Uffe Høgsbro

AU - Baktoft,Henrik

AU - Madsen,Henrik

PB - DTU Informatics, Building 321

PY - 2010

Y1 - 2010

N2 - A hierarchical framework for simultaneous analysis of multiple related individual datasets is presented. The approach is very similar to mixed effects modelling as known from statistical theory. The model used at the individual level is, in principle, irrelevant as long as a maximum likelihood estimate and its uncertainty (Hessian) can be computed. The individual model used in this text is a hidden Markov model. A simulation study concerning a two-dimensional biased random walk is examined to verify the consistency of the hierarchical estimation framework. In addition, a study based on acoustic telemetry data from pike illustrates how the framework can identify individuals that deviate from the remaining population.

AB - A hierarchical framework for simultaneous analysis of multiple related individual datasets is presented. The approach is very similar to mixed effects modelling as known from statistical theory. The model used at the individual level is, in principle, irrelevant as long as a maximum likelihood estimate and its uncertainty (Hessian) can be computed. The individual model used in this text is a hidden Markov model. A simulation study concerning a two-dimensional biased random walk is examined to verify the consistency of the hierarchical estimation framework. In addition, a study based on acoustic telemetry data from pike illustrates how the framework can identify individuals that deviate from the remaining population.

BT - Individual based population inference using tagging data

T3 - IMM-Technical Report-2010-11

T3 - en_GB

ER -