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We consider the problem of detecting changes in a multivariate data stream. A change detector is defined by a detection algorithm and an alarm threshold. A detection algorithm maps the stream of input vectors into a univariate detection stream. The detector signals a change when the detection stream exceeds the chosen alarm threshold. We consider two(More)
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the discipines of mathematics, statistics and computer science. These guidelines are(More)
Cluster detection is an important public health endeavor, and in this article, we describe and apply a recently developed Bayesian method. Commonly used approaches are based on so-called scan statistics and suffer from a number of difficulties, which include how to choose a level of significance and how to deal with the possibility of multiple clusters. The(More)
The embryonic precursor of the vertebrate central nervous system, the neural plate, is patterned along the anterior-posterior axis and shaped by morphogenetic movements early in development. We previously identified the genes sall1 and sall4, known regulators of pluripotency in other contexts, as transcriptional targets of developmental signaling pathways(More)
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