A realistic radar scattering model to predict backscattering cross section for different frequencies and polarizations is an important tool for understanding the relationship between radar measurement and forest properties, and for enabling the estimation of forest parameters from radar data. Popular, conventional models typically specify a two-layer discrete random medium placed on a continuou...

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such a...

Classification is the process of assigning a class label to an observation based on its proprieties or attributes. A classification algorithm is applied to a data set, producing a model. By studying the model, insights about the data set structure can be gained. The benefits that a model can bring depend on the model. In this work, a Random Forest model is used for the analysis of data. A Rando...

We develop new modeling for personalized treatment for longitudinal studies involving high heterogeneity of treatment effects. Incorporating subject-specific information into the treatment assignment is crucial since different individuals can react to the same treatment very differently. We estimate unobserved subject-specific treatment effects through conditional random-effects modeling, and a...

Methods: We searched multiple databases through May 2010 for studies evaluating the performance of the newest commercial IGRAs (QuantiFERON-TB Gold In-Tube [QFT-GIT] and T-SPOT.TB [TSPOT]) in HIV-infected individuals. We assessed the quality of all studies included in the review, summarized results in prespecified subgroups using forest plots, and where appropriate, calculated pooled estimates ...

One of the most famous results in the theory of random graphs establishes that the threshold for Hamiltonicity in the Erdős-Rényi random graph Gn,p is around p ∼ logn+log logn n . Much research has been done to extend this to increasingly challenging random structures. In particular, a recent result by Frieze determined the asymptotic threshold for a loose Hamilton cycle in the random 3-uniform...

This paper proposes a distributional model of word use and word meaning which is derived purely from a body of text, and then applies this model to determine whether certain words are used in or out of context. We suggest that we can view the contexts of words as multinomially distributed random variables. We illustrate how using this basic idea, we can formulate the problem of detecting whethe...