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Full-Text Articles in Physical Sciences and Mathematics
Improving Accuracy Of Large-Scale Prediction Of Forest Disease Incidence Through Bayesian Data Reconciliation, Ephraim M. Hanks
Improving Accuracy Of Large-Scale Prediction Of Forest Disease Incidence Through Bayesian Data Reconciliation, Ephraim M. Hanks
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Increasing the accuracy of predictions made from ecological data typically involves replacing or replicating the data, but the cost of updating large-scale data sets can be prohibitive. Focusing resources on a small sample of locations from a large, less accurate data set can result in more reliable observations, though on a smaller scale. We present an approach for increasing the accuracy of predictions made from a large-scale eco logical data set through reconciliation with a small, highly accurate data set within a Bayesian hierarchical modeling framework. This approach is illustrated through a study of incidence of eastern spruce dwarf mistletoe …