5 papers
Locally sharp goodness-of-fit testing in sup norm for high-dimensional counts
Subhodh Kotekal, Julien Chhor, Chao Gao
We consider testing the goodness-of-fit of a distribution against alternatives separated in sup norm. We study the twin settings of Poisson-generated count data with a large number…
Optimal estimation of the null distribution in large-scale inference
Subhodh Kotekal, Chao Gao
The advent of large-scale inference has spurred reexamination of conventional statistical thinking. In a Gaussian model for many -scores with at most nonnu…
Sparsity meets correlation in Gaussian sequence model
Subhodh Kotekal, Chao Gao
We study estimation of an -sparse signal in the -dimensional Gaussian sequence model with equicorrelated observations and derive the minimax rate. A new phenomenon emerges fr…
Minimax Signal Detection in Sparse Additive Models
Subhodh Kotekal, Chao Gao
Sparse additive models are an attractive choice in circumstances calling for modelling flexibility in the face of high dimensionality. We study the signal detection problem and est…
Minimax rates for sparse signal detection under correlation
Subhodh Kotekal, Chao Gao
We fully characterize the nonasymptotic minimax separation rate for sparse signal detection in the Gaussian sequence model with equicorrelated observations, generalizing a resu…