Web: http://arxiv.org/abs/2007.07781

June 23, 2022, 1:12 a.m. | Sokbae Lee, Serena Ng

stat.ML updates on arXiv.org arxiv.org

Researchers may perform regressions using a sketch of data of size $m$
instead of the full sample of size $n$ for a variety of reasons. This paper
considers the case when the regression errors do not have constant variance and
heteroskedasticity robust standard errors would normally be needed for test
statistics to provide accurate inference. We show that estimates using data
sketched by random projections will behave `as if' the errors were
homoskedastic. Estimation by random sampling would not have …

arxiv data errors least ml squares

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