BMF Collaborative Project 17: Meeting demand for renewable biomass energy through private landowners’ wasted resources

Abstract

The research project will employ the mindsponge theory for conceptual development and Bayesian Mindsponge Framework (BMF) analytics for statistical analysis on the dataset of 707 private landowners in two SE US fuel sheds that supply most of the wood pellets exported to the EU. The bayesvl R package, aided by the Markov chain Monte Carlo (MCMC) algorithm, will be employed for statistical analyses. All the materials and codes for this study will be made available only to reduce the cost of doing science and to provide transparency. For more information on BMF analytics, portal users can refer to the following book.