@article{Gorddard:170820,
      recid = {170820},
      author = {Gorddard, Russell},
      title = {A Bayesian State Space Approach to Estimating Pest  Management Models},
      address = {1995-02},
      number = {406-2016-25265},
      pages = {16},
      year = {1995},
      abstract = {Models for pest management need to incorporate information  from many subject areas,
including biology, agronomy and  economics. The information sources are unrelated except
by  the structural assumptions of the bio-economic model that  is used. Rigorous model
estimation is often at the expense  of ignoring much of the available information. This
paper  illustrates how a Bayesian approach using the Gibbs sampler  can allow the
incorporation of potentially valuable prior  information. This approach provides posterior
distributions  for the important model relationships, giving an indication  of confidence in
the model and providing a natural starting  point for stochastic decision making.},
      url = {http://ageconsearch.umn.edu/record/170820},
      doi = {https://doi.org/10.22004/ag.econ.170820},
}