Roland Langrock
@rolandlangrock.bsky.social
Statistician @BielefeldUniversity, working mostly on HMMs, statistical ecology, sports data. But teaching is even more fun.
Reposted by Roland Langrock
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...
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
September 5, 2025 at 12:06 PM
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...
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...
Reposted by Roland Langrock
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. 🧪
We combine Gaussian processes + hidden Markov models to efficiently detect stellar flares in one modelling step. 🧪
January 31, 2025 at 2:26 AM
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. 🧪
We combine Gaussian processes + hidden Markov models to efficiently detect stellar flares in one modelling step. 🧪
Reposted by Roland Langrock
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
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
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...
arxiv.org
December 25, 2024 at 4:30 PM
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
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