Statistical Challenges in Online Controlled Experiments: A Review of A/B Test…
The rise of internet-based services and products in the late 1990s brought about an unprecedented opportunity for online businesses to engage in large scale data-driven decision making. Over the pa…
D- and A-Optimal Screening Designs
In practice, optimal screening designs for arbitrary run sizes are traditionally generated using the D-criterion with factor settings fixed at ±1, even when considering continuous factors with lev…
Incorporating Minimum Variances into Weighted Optimality Criteria
Weighted optimality criteria allow an experimenter to express hierarchical interest across estimable functions through a concise weighting system. We show how such criteria can be implicitly influe…
Strategies for Supersaturated Screening : Group Orthogonal and Constrained Va…
Despite the vast amount of literature on supersaturated designs (SSDs), there is a scant record of their use in practice. We contend this imbalance is due to conflicting recommendations regarding S…
Sequential Optimization in Locally Important Dimensions
Optimizing an expensive, black-box function f(⋅) is challenging when its input space is high-dimensional. Sequential design frameworks first model f(⋅) with a surrogate function and then optimi…
Construction, Properties, and Analysis of Group-Orthogonal Supersaturated Des…
In this article, we propose a new method for constructing supersaturated designs that is based on the Kronecker product of two carefully chosen matrices. The construction method leads to a partitio…
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