2 citations · 2 across the 3 of their papers we have counts for
6 papers
The Discrete Adjoint Method: Efficient Derivatives for Functions of Discrete Sequences
Michael Betancourt, Charles C. Margossian, Vianey Leos-Barajas
Gradient-based techniques are becoming increasingly critical in quantitative fields, notably in statistics and computer science. The utility of these techniques, however, ultimatel…
Approximate Bayesian inference for a "steps and turns" continuous-time random walk observed at regular time intervals
Sofia Ruiz-Suarez, Vianey Leos-Barajas, Ignacio Alvarez-Castro +1
The study of animal movement is challenging because it is a process modulated by many factors acting at different spatial and temporal scales. Several models have been proposed whi…
An Introduction to Animal Movement Modeling with Hidden Markov Models using Stan for Bayesian Inference
Vianey Leos-Barajas, Théo Michelot
Hidden Markov models (HMMs) are popular time series model in many fields including ecology, economics and genetics. HMMs can be defined over discrete or continuous time, though her…
The Hot Hand in Professional Darts
Marius Ötting, Roland Langrock, Christian Deutscher +1
We investigate the hot hand hypothesis in professional darts in a near-ideal setting with minimal to no interaction between players. Considering almost one year of tournament data,…
Multi-scale modeling of animal movement and general behavior data using hidden Markov models with hierarchical structures
Vianey Leos-Barajas, Eric Gangloff, Timo Adam +4
Hidden Markov models (HMMs) are commonly used to model animal movement data and infer aspects of animal behavior. An HMM assumes that each data point from a time series of observat…
Analysis of animal accelerometer data using hidden Markov models
Vianey Leos-Barajas, Theoni Photopoulou, Roland Langrock +4
Use of accelerometers is now widespread within animal biotelemetry as they provide a means of measuring an animal's activity in a meaningful and quantitative way where direct obser…