1 citations · 1 across the 2 of their papers we have counts for
3 papers
math.ST2025
Tracy-Widom, Gaussian, and Bootstrap: Approximations for Leading Eigenvalues in High-Dimensional PCA
Nina Dörnemann, Miles E. Lopes
Under certain conditions, the largest eigenvalue of a sample covariance matrix undergoes a well-known phase transition when the sample size and data dimension diverge propo…
stat.ME2024
Robust Max Statistics for High-Dimensional Inference
Mingshuo Liu, Miles E. Lopes
Although much progress has been made in the theory and application of bootstrap approximations for max statistics in high dimensions, the literature has largely been restricted to…
math.ST2021★ 1 cited
Rates of Bootstrap Approximation for Eigenvalues in High-Dimensional PCA
Junwen Yao, Miles E. Lopes
In the context of principal components analysis (PCA), the bootstrap is commonly applied to solve a variety of inference problems, such as constructing confidence intervals for the…