Author

Tate Jacobson

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Preprint Oct 2026

Global Inference for High Dimensional Quantile Regression with Heterogeneity

Quantile regression has received considerable attention in high dimensional methodology due to its robustness and ability to accommodate heteroskedasticity. Despite this attention, current inferential methods for high dimensional quantile regression have significant limitations---only testing significance, testing at a...

Tate Jacobson, Daeyoung Ham, Ben Sherwood · 0 citations

Preprint Oct 2026

Large-scale linear hypothesis testing for high-dimensional online M-estimation

With the growing prevalence of streaming data, renewable estimation has become an important tool for updating statistical analyses without retaining historical raw observations. We study estimation and linear hypothesis testing in high-dimensional online M-estimation. Existing renewable procedures based on quadratic ap...

D. Ham, Myeonghun Yu, Tate Jacobson · 0 citations