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Motivated by applications in neuroanatomy, we propose a novel methodology to estimate heritability, which corresponds to the proportion of phenotypic variance that can be explained by genetic factors. Since the phenotypic variations may be due to only a small fraction of the available genetic information, we propose an estimator of heritability that can be used in sparse linear mixed models. Since...
We study a problem of model selection for data produced by two different context tree sources. Motivated by linguistic questions, we consider the case where the probabilistic context trees corresponding to the two sources are finite and share many of their contexts. In order to understand the differences between the two sources, it is important to identify which contexts and which transition probabilities...
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