= Yen-Chi Chen
{c}
<Yen-Chi Chen> works on <nonparametric statistics>, <Causal inference>, <missing data> and <geometric data analysis>[geometric analysis of data]. His University of Washington research page also lists <mixture model>[mixture models], astrostatistics and applied statistics.https://faculty.washington.edu/yenchic/[Author homepage, Research Interests]{ref}
His bootstrap notes explain the distinction between the unknown population distribution and the <empirical distribution> used for resampling. They also discuss when a bootstrap approximation can fail, including an endpoint of a <uniform distribution>. This is a useful bridge between a computational recipe and the mathematical conditions needed for reliable statistical inference.<UW STAT 535: Statistical Machine Learning, Autumn 2026/Lecture 12: The Bootstrap>[The Bootstrap; High level idea of how bootstrap works; Failure of the bootstrap]{ref}
Homepage: https://faculty.washington.edu/yenchic/
\Image[https://faculty.washington.edu/yenchic/images/photo101017.png]
{title=Yen-Chi Chen}
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