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Collaborative Design of Controlled Experiments in the Presence of Subject Covariates

存在受试者协变量时受控实验的协同设计

We consider the optimal experimental design problem of allocating subjects to treatment or control when subjects participate in multiple, separate controlled experiments within a short time-frame and subject covariate information is available. Here, in addition to subject covariates, we consider the dependence among the responses coming from the subject's random effect across experiments. In this setting, the goal of the allocation is to provide precise estimates of…

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Neighborhood VAR: Efficient estimation of multivariate timeseries with neighborhood information

邻域 VAR:利用邻域信息高效估计多元时间序列

In data science, vector autoregression (VAR) models are popular in modeling multivariate time series in the environmental sciences and other applications. However, these models are computationally complex with the number of parameters scaling quadratically with the number of time series. In this work, we propose a so-called neighborhood vector autoregression (NVAR) model to efficiently analyze large-dimensional multivariate time series. We assume that the time series have…

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