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stat.ME2026
Detection of Structural Distortions in Functional Time Series
Debanjana Datta, Rituparna Sen, Nalini Ravishanker
In the era of modern data science, the rapid proliferation of high-dimensional and functional datasets has fostered increasing interest in the investigation of paradigm shifts and…
math.ST2026
A Frequentist Approach to Change Point Detection: Methods and Applications
Debanjana Datta
In this paper we study the problem of change point detection in functional time series where the observations are allowed to vary on both sparse and dense support. We address the p…
math.ST2026
Measuring Tail Dependence in Linear Processes: Theory and Empirics
Debanjana Datta, Diganta Mukherjee
The quantitative analysis of financial time series often reveals two distinct features that standard Gaussian frameworks fail to capture: heavy-tailed marginal distributions and th…