Lynn

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🐢🗺️

07.01.2026 09:58 — 👍 4    🔁 2    💬 0    📌 1

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.

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

10.12.2025 14:53 — 👍 13    🔁 5    💬 1    📌 0

Hidden semi-Markov models with inhomogeneous state dwell-time distributions The well-established methodology for the estimation of hidden semi-Markov models (HSMMs) as hidden Markov models (HMMs) with extended state spaces is …

My paper is out! 🎉 I explore hidden semi-Markov models with covariate-dependent state dwell-time distributions — because sometimes Markov just isn’t enough.
Case study: Arctic muskox movement! 🦬📊
🔗 www.sciencedirect.com/science/arti...

#stats #TimeSeries #HSMM #StatisticalEcology #rstats

19.03.2025 16:35 — 👍 8    🔁 2    💬 1    📌 0

Good luck! 🏈🇺🇸

07.01.2025 14:13 — 👍 2    🔁 0    💬 0    📌 0