@article{Ticlavilca:285320,
      recid = {285320},
      author = {Ticlavilca, Andres M. and Feuz, Dillon M.},
      title = {Forecasting Agricultural Commodity Prices Using  Multivariate Bayesian Machine},
      address = {2010-04},
      series = {NCCC-134 Applied Commodity Price Analysis, Forecasting,  and Market Risk Management},
      year = {2010},
      abstract = {The purpose of this paper is to perform multiple  predictions for agricultural commodity prices (one, two and  three month periods ahead). In order to obtain  multiple-time-ahead predictions, this paper applies the  Multivariate Relevance Vector Machine (MVRVM) that is based  on a Bayesian learning machine approach for regression. The  performance of the MVRVM model is compared with the  performance of another multiple output model such as  Artificial Neural Network (ANN). Bootstrapping methodology  is applied to analyze robustness of the MVRVM and ANN.},
      url = {http://ageconsearch.umn.edu/record/285320},
      doi = {https://doi.org/10.22004/ag.econ.285320},
}