Session | ||
TA9 - SM3: Estimation and optimization for services
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Presentations | ||
Optimal experimental design for staggered rollouts 1Emory University; 2Stanford University We study the problem of designing experiments that are conducted on a set of units, such as users in an online marketplace, for multiple time periods. We first study the optimal design of experiments, to most precisely estimate the instantaneous and lagged effects, post-experiment, when treatment decisions are made before the experiment starts. Next, we study the design of sequential experiments, where adaptive decisions are allowed, and the experiments can potentially be stopped early. Robust queue inference: consistent estimators from partially observed data 1Southern Methodist University, United States of America; 2National University of Singapore, Singapore; 3Northwestern University, United States of America While observational data from queueing system is of great interest for statistical inference of arrival and service processes, the queueing dynamics and the absence of distributional information render queue estimation remarkably challenging. To this end, we propose a robust optimization based framework for inferring service times from waiting time observations. We provide conditions under which our framework produces statistically consistent estimators and present its managerial insights. |