Predicting Fusarium Head Blight Epidemics with Boosted Regression Trees

Fusarium Head Blight of Wheat

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Boosted regression trees with errors in variables.

In this article, we consider nonparametric regression when covariates are measured with error. Estimation is performed using boosted regression trees, with the sum of the trees forming the estimate of the conditional expectation of the response. Both binary and continuous response regression are investigated. An approach to fitting regression trees when covariates are measured with error is des...

Boosted Regression Trees for ecological modeling

This is a brief tutorial to accompany a set of functions that we have written to facilitate fitting BRT (boosted regression tree) models in R . This tutorial is a modified version of the tutorial accompaniying Elith, Leathwick and Hastie’s article in Journal of Animal Ecology. It has been adjusted to match the implementation of these functions in the ’dismo’ package. The gbm* functions in the d...

A working guide to boosted regression trees.

1. Ecologists use statistical models for both explanation and prediction, and need techniques that are flexible enough to express typical features of their data, such as nonlinearities and interactions. 2. This study provides a working guide to boosted regression trees (BRT), an ensemble method for fitting statistical models that differs fundamentally from conventional techniques that aim to fi...

Predicting Fusarium Head Blight and the Accumulation of Associated Mycotoxins under Climate Change