3 papers
stat.ME2020
Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models
Lennart Oelschläger, Timo Adam
Financial markets exhibit alternating periods of rising and falling prices. Stock traders seeking to make profitable investment decisions have to account for those trends, where th…
stat.ME2019
Penalized estimation of flexible hidden Markov models for time series of counts
Timo Adam, Roland Langrock, Christian H. Weiß
Hidden Markov models are versatile tools for modeling sequential observations, where it is assumed that a hidden state process selects which of finitely many distributions generate…
stat.ME2017
Multi-scale modeling of animal movement and general behavior data using hidden Markov models with hierarchical structures
Vianey Leos-Barajas, Eric Gangloff, Timo Adam +4
Hidden Markov models (HMMs) are commonly used to model animal movement data and infer aspects of animal behavior. An HMM assumes that each data point from a time series of observat…