Several methods exist in classification literature to quantify the similarity between two time
series data sets. Applications of these methods range from the traditional Euclidean-type …

Count time series data with excess zeros are observed in several applied disciplines. When
these zero-inflated counts are sequentially recorded, they might result in serial dependence …

In this paper, we propose a novel approach for classifying incoming continuous data under a
non-stationary environment. A class of estimators termed stochastic learning weak …

Rare events are plentiful in nature and most of them have devastating consequences on
human lives and property. Modeling such events is intrinsically challenging due to their very …

In computer science, stochastic processes, and industrial engineering, stationarity is often
taken to imply a stable, predictable flow of events and non-stationarity, consequently, a …

Hawaiian volcanoes such as Kilauea and Mauna Loa have drawn the attention of
researchers for quite some time and numerous theories abound hinting at a possible inverse …

To a practitioner who chooses to test the robustness while keeping track of all the
perspectives, angles, and elements of a study's conclusions in the data analysis, we offer an …

Abstract Hidden Markov models (HMMs), especially those with a Poisson density governing
the latent state-dependent emission probabilities, have enjoyed substantial and undeniable …

Finance is the industry that rules the world, and banks, by and large, represent a great
percentage of that industry. After the financial crisis, public cries for a more stable financial …

Hurricanes originating in the West Atlantic often have devastating consequences on the
cities in the US east coast, both monetary and otherwise, and hence pose a source of …