Jan. 1, 2022, midnight | Ping Ma, Yongkai Chen, Xinlian Zhang, Xin Xing, Jingyi Ma, Michael W. Mahoney

JMLR www.jmlr.org

The statistical analysis of Randomized Numerical Linear Algebra (RandNLA) algorithms within the past few years has mostly focused on their performance as point estimators. However, this is insufficient for conducting statistical inference, e.g., constructing confidence intervals and hypothesis testing, since the distribution of the estimator is lacking. In this article, we develop an asymptotic analysis to derive the distribution of RandNLA sampling estimators for the least-squares problem. In particular, we derive the asymptotic distribution of a general sampling estimator with …

algorithms analysis linear linear algebra numerical sampling

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