3 papers
math.PR2026
Clustering of large deviations in heavy-tailed moving averages: the catastrophe principle in the long-memory case
Jiaqi Wang, Gennady Samorodnitsky
Clustering of large deviations events in a stationary stochastic process depends critically on the interplay between the tail behavior of the marginal distribution and the strength…
math.PR2025
Clustering of large deviations events in heavy-tailed moving average processes: the catastrophe principle in the short-memory case
Jiaqi Wang, Gennady Samorodnitsky
How do large deviation events in a stationary process cluster? The answer depends not only on the type of large deviations, but also on the length of memory in the process. Somewha…
stat.ME2025
Likelihood Inference for Possibly Non-Stationary Processes via Adaptive Overdifferencing
Maryclare Griffin, Gennady Samorodnitsky, David S. Matteson
We make an observation that facilitates exact likelihood-based inference for the parameters of the popular ARFIMA model without requiring stationarity by allowing the upper bound $…