iiinova — where your digital self keeps evolving

Roland Langrock @rolandlangrock.bsky.social · 29/05/2026

We are looking for participants for our study World Cup Fever, which aims to investigate the physiological responses of fans from different nationalities to the course of matches. Please share widely 🙏 www.uni-bielefeld.de/einrichtunge...

uni-bielefeld.de

World Cup Fever - Universität Bielefeld

Wir analysieren die

051

Reposted by Roland Langrock

Jan-Ole Fischer @olemole.bsky.social · 23/03/2026

New preprint 📑 Fast inference in HMMs with latent Gaussian fields (via SPDE approach + RTMB) ⚡️ 🔗 arxiv.org/abs/2603.17469 We modify the forward algorithm to recover a sparse Hessian ➡️ Fast automatic Laplace approximation Case studies: 1) Detecting stellar flares 2) Lion movement w spatial field

1133

Reposted by Roland Langrock

Maya Vienken @mayavienken.bsky.social · 07/01/2026

We have a new preprint on covariate-driven #HMMs! doi.org/10.48550/arX... @olemole.bsky.social, @rolandlangrock.bsky.social • commonly used hypothetical stationary distribution can be biased⚠️ • we propose 2 approaches allowing unbiased inference • simulations and case study on Galápagos tortoises🐢🗺️

063

Roland Langrock @rolandlangrock.bsky.social · 07/01/2026

Very proud of this paper, where we show that what I've been teaching folks for years is actually really not such a clever thing to do 🙈 But we also provide solutions 💪 Also what a way to kick-start your PhD, @mayavienken.bsky.social 👑

040

Reposted by Roland Langrock

Jan-Ole Fischer @olemole.bsky.social · 10/12/2025

Our paper on #HMMs with periodically ⏰ varying transition probabilities is published! 🎉 @carlinafeldmann.bsky.social, Sina Mews, @rmichels.bsky.social @rolandlangrock.bsky.social doi.org/10.1214/25-AOAS2107 We derive the periodically #stationary distribution and the implied dwell-time distribution

Periodically stationary distribution (probability that the fly is active) as a function of the time of day.
True stationary distribution is compared to biased approximation, and we see a substantial difference.

1155

Reposted by Roland Langrock

Jan-Ole Fischer @olemole.bsky.social · 05/09/2025

Our review paper on latent Markov models is now published in Statistical Modelling! 🎉 @rolandlangrock.bsky.social @SinaMews. We discuss choosing the right time and space formulation and provide the R package 📦 LaMa for fast ⚡and flexible estimation. 📄 Paper: journals.sagepub.com/eprint/UETXX...

sagepub.com

1121

Reposted by Roland Langrock

Vianey Leos Barajas @vianeylb.bsky.social · 31/01/2025

The world is on 🔥 -- and here's my first publication in an astronomy journal: iopscience.iop.org/article/10.3... We combine Gaussian processes + hidden Markov models to efficiently detect stellar flares in one modelling step. 🧪

2399

Reposted by Roland Langrock

Jan-Ole Fischer @olemole.bsky.social · 25/12/2024

Sina Mews, Roland Langrock, and I have updated 🆕 our review paper! It offers a comprehensive overview on choosing the right time ⏰ and space 📏 formulation for latent Markov models, providing a unifying perspective on discrete- and continuous-time HMMs, SSMs and MMPPs. 👉 arxiv.org/abs/2406.19157

arxiv.org

How to build your latent Markov model -- the role of time and space

Statistical models that involve latent Markovian state processes have become immensely popular tools for analysing time series and other sequential data. However, the plethora of model formulations, t...

1166