I bet you love penguins, right? The same goes for koalas, or puppies! But what about sharks? Well, my next guest loves sharks — she loves them so much that she works a lot with marine biologists, even though she’s a statistician! 
Vianey Leos Barajas is indeed a statistician primarily working in the areas of statistical ecology, time series modeling, Bayesian inference and spatial modeling of environmental data. Vianey did her PhD in statistics at Iowa State University and is now a postdoctoral researcher at North Carolina State University.
In this episode, she’ll tell us what she’s working on that involves sharks, sheep and other animals! Trying to model animal movements, Vianey often encounters the dreaded multimodal posteriors. She’ll explain why these can be very tricky to estimate, and why ecological data are particularly suited for hidden Markov models and spatio-temporal models — don’t worry, Vianey will explain what these models are in the episode!
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ (https://bababrinkman.com/) !
Links from the show:
Vianey on Twitter: https://twitter.com/vianey_lb (https://twitter.com/vianey_lb)
Hidden Markov Models in the Stan User's Guide: https://mc-stan.org/docs/2_18/stan-users-guide/hmms-section.html (https://mc-stan.org/docs/2_18/stan-users-guide/hmms-section.html)
Tagging Basketball Events with HMM in Stan: https://mc-stan.org/users/documentation/case-studies/bball-hmm.html (https://mc-stan.org/users/documentation/case-studies/bball-hmm.html)
HMMs with Python and PyMC3: https://ericmjl.github.io/bayesian-analysis-recipes/notebooks/markov-models/
The Discrete Adjoint Method -- Efficient Derivatives for Functions of Discrete Sequences (Betancourt, Margossian, Leos-Barajas): https://arxiv.org/abs/2002.00326 (https://arxiv.org/abs/2002.00326)
Vianey will be doing an HMM 90-minute introduction at the International Statistical Ecology Conference in June 2020: http://www.isec2020.org/ (http://www.isec2020.org/)
Stan for Ecology -- a website for the ecology community in Stan: https://stanecology.github.io/ (https://stanecology.github.io/)
LatinR 2020 -- 7th to 9th October 2020: https://latin-r.com/ (https://latin-r.com/)
Migramar -- Science for the Conservation of Marine Migratory Species in the Eastern Pacific: http://migramar.org/hi/en/ (http://migramar.org/hi/en/)
Pelagios Kakunja -- Know, educate and conserve for a sustainable sea: https://www.pelagioskakunja.org/ (https://www.pelagioskakunja.org/)

Book recommendations:
Hidden Markov Models for Time Series: https://www.routledge.com/Hidden-Markov-Models-for-Time-Series-An-Introduction-Using-R-Second-Edition/Zucchini-MacDonald-Langrock/p/book/9781482253832 (https://www.routledge.com/Hidden-Markov-Models-for-Time-Series-An-Introduction-Using-R-Second-Edition/Zucchini-MacDonald-Langrock/p/book/9781482253832)
Handbook of Mixture Analysis: https://www.routledge.com/Handbook-of-Mixture-Analysis-1st-Edition/Fruhwirth-Schnatter-Celeux-Robert/p/book/9781498763813 (https://www.routledge.com/Handbook-of-Mixture-Analysis-1st-Edition/Fruhwirth-Schnatter-Celeux-Robert/p/book/9781498763813)
Pattern Recognition and Machine Learning: http://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf (http://users.isr.ist.utl.pt/~wurmd/Livros/school/Bishop%20-%20Pattern%20Recognition%20And%20Machine%20Learning%20-%20Springer%20%202006.pdf)



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