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受多臂老虎机启发的模型不确定性下最优设计AI 解读

An optimal design is usually model-dependent and is sub-optimal if the postulated model is not correctly specified. Furthermore, it is far from ideal even if it is efficient for model selection but has a poor performance for estimating parameters in the selected model. In practice, it is common that a researcher has a list of candidate models at hand and a design has to be found that is efficient for both model discrimination and parameter estimation in the (unknown) “true”…

海量数据下最大准似然估计的最优分布式子抽样AI 解读

Nonuniform subsampling methods are effective to reduce computational burden and maintain estimation efficiency for massive data. Existing methods mostly focus on subsampling with replacement due to its high computational efficiency. If the data volume is so large that nonuniform subsampling probabilities cannot be calculated all at once, then subsampling with replacement is infeasible to implement. This article solves this problem using Poisson subsampling. We first derive…

干扰模型中普遍最优圆周设计的判别AI 解读

Many applications of block designs exhibit neighbor and edge effects. A popular remedy is to use the circular design coupled with the interference model. The search for optimal or efficient designs has been intensively studied in recent years. The circular neighbor balanced designs at distances 1 and 2 (CNBD2), including orthogonal array of type I ($\mathrm{OA}_{I}$) of strength $2$, are the two major designs proposed in literature for the purpose of estimating the direct…

嵌套格点抽样：随机化嵌套正交表的新抽样方案AI 解读

A nested orthogonal array is an orthogonal array that contains a smaller orthogonal array as a subarray. We construct a new sampling scheme, called nested lattice sampling, by randomizing nested orthogonal arrays with nested permutations. For a pair of nested lattice samples associated with a nested orthogonal array of strength t, the points in both samples achieve uniformity in t or lower dimensions. Some statistical properties of nested lattice samples based on strength…