5 papers · 1 filter
A Spectral Boundary for Independence Learnability
Senhan Yao, Yuxin Zhou
Learning independence is fundamental to statistical inference and machine learning, yet learning independence between entire time series by a test remains challenging when only a s…
Strongly Consistent Estimation of the Extended -Sum of -Mixing Coefficients from a Single Trajectory
Senhan Yao
Khaleghi and Lugosi asked whether the sum of the -mixing (uniform-mixing) coefficients of a real-valued discrete-time stationary ergodic process can be consistently estimated fr…
Independence Is Not Always Consistently Testable
Senhan Yao
We study the problem of testing independence between the coordinate processes of a jointly stationary ergodic binary process from finite observations. We prove that no test is poin…
Uniform Testability Implies Asymmetric Testability
Senhan Yao
We prove a filtration-level conversion from uniform fixed-time testing to all-sample one-sided error control and uniform future-tail control. Given an adapted deterministic binary…
Weak but Not Strong Asymptotic Testability
Senhan Yao
We construct two fixed disjoint families of stationary ergodic binary process distributions for which a weakly asymptotically consistent test exists, but no strongly asym…