11 papers
Maximum approximate likelihood estimation of general continuous-time state-space models
Sina Mews, Roland Langrock, Marius Ötting +2
Continuous-time state-space models (SSMs) are flexible tools for analysing irregularly sampled sequential observations that are driven by an underlying state process. Corresponding…
A primer on coupled state-switching models for multiple interacting time series
Jennifer Pohle, Roland Langrock, Mihaela van der Schaar +2
State-switching models such as hidden Markov models or Markov-switching regression models are routinely applied to analyse sequences of observations that are driven by underlying n…
Uncovering ecological state dynamics with hidden Markov models
Brett T. McClintock, Roland Langrock, Olivier Gimenez +4
Ecological systems can often be characterised by changes among a finite set of underlying states pertaining to individuals, populations, communities, or entire ecosystems through t…
A copula-based multivariate hidden Markov model for modelling momentum in football
Marius Ötting, Roland Langrock, Antonello Maruotti
We investigate the potential occurrence of change points - commonly referred to as "momentum shifts" - in the dynamics of football matches. For that purpose, we model minute-by-min…
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…
Very Highly Skilled Individuals Do Not Choke Under Pressure: Evidence from Professional Darts
Christian Deutscher, Marius Ötting, Roland Langrock +3
Understanding and predicting how individuals perform in high-pressure situations is of importance in designing and managing workplaces, but also in other areas of society such as d…