Cristina Cornelio, Judy Goldsmith, et al.
JAIR
This paper studies Central Limit Theorems for real-valued functionals of Conditional Markov Chains. Using a classical result by Dobrushin (1956) for non-stationary Markov chains, a conditional Central Limit Theorem for fixed sequences of observations is estab- lished. The asymptotic variance can be es- timated by resampling the latent states con- ditional on the observations. If the condi- tional means themselves are asymptotically normally distributed, an unconditional Cen- tral Limit Theorem can be obtained. The methodology is used to construct a statistical hypothesis test which is applied to syntheti- cally generated environmental data.
Cristina Cornelio, Judy Goldsmith, et al.
JAIR
Amarachi Blessing Mbakwe, Joy Wu, et al.
NeurIPS 2023
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
Paula Harder, Venkatesh Ramesh, et al.
EGU 2023