Jan-Ole Koslik
@olemole.bsky.social
PhD student 🎓 in Statistics at Bielefeld University interested in doubly stochastic processes and their application to ecology 🦅, sports 🏈, and finance 📈.
Website: https://janoleko.github.io
GitHub: https://github.com/janoleko
Website: https://janoleko.github.io
GitHub: https://github.com/janoleko
And that assessment is totally unbiased ofc 😂
December 10, 2025 at 3:26 PM
And that assessment is totally unbiased ofc 😂
Using #simulations and a case study on #fruitflies 🪰, we show that
- the widely used stationary approximation can be severely biased! ❌
- dwell-time distributions can deviate substantially from a #geometric shape.
#HMM #MarkovChain #seasonality #diel #stats #rstats #StatisticalEcology #behaviour
- the widely used stationary approximation can be severely biased! ❌
- dwell-time distributions can deviate substantially from a #geometric shape.
#HMM #MarkovChain #seasonality #diel #stats #rstats #StatisticalEcology #behaviour
December 10, 2025 at 2:54 PM
Using #simulations and a case study on #fruitflies 🪰, we show that
- the widely used stationary approximation can be severely biased! ❌
- dwell-time distributions can deviate substantially from a #geometric shape.
#HMM #MarkovChain #seasonality #diel #stats #rstats #StatisticalEcology #behaviour
- the widely used stationary approximation can be severely biased! ❌
- dwell-time distributions can deviate substantially from a #geometric shape.
#HMM #MarkovChain #seasonality #diel #stats #rstats #StatisticalEcology #behaviour
The LaMa package provides a versatile framework for inference with latent Markov models, designed to make building such models fun and efficient.
Check out the vignettes and start building models! 🛠️
👉 janoleko.github.io/LaMa/
Check out the vignettes and start building models! 🛠️
👉 janoleko.github.io/LaMa/
Fast Numerical Maximum Likelihood Estimation for Latent Markov Models
A variety of latent Markov models, including hidden Markov models, hidden semi-Markov models, state-space models and continuous-time variants can be formulated and estimated within the same framework ...
janoleko.github.io
September 5, 2025 at 12:10 PM
The LaMa package provides a versatile framework for inference with latent Markov models, designed to make building such models fun and efficient.
Check out the vignettes and start building models! 🛠️
👉 janoleko.github.io/LaMa/
Check out the vignettes and start building models! 🛠️
👉 janoleko.github.io/LaMa/
All the relevant methodology is fully implemented 🛠️ in my R package LaMa 🦙:
janoleko.github.io/LaMa/
janoleko.github.io/LaMa/
Fast Numerical Maximum Likelihood Estimation for Latent Markov Models
A variety of latent Markov models, including hidden Markov models, hidden semi-Markov models, state-space models and continuous-time variants can be formulated and estimated within the same framework ...
janoleko.github.io
March 19, 2025 at 4:35 PM
All the relevant methodology is fully implemented 🛠️ in my R package LaMa 🦙:
janoleko.github.io/LaMa/
janoleko.github.io/LaMa/