… Recent developments in modelling movement as a continuous-time stochastic process (CTSP)
solve these problems, but the mathematical difficulty of using CTSPs has limited their …

… analyses to the evergrowing number of modern datasets that feature thousands or more
observed animal locations, and they are key to the continuous-time movement modeling (ctmm) …

… Extending existing continuous-time stochastic movement models, we … ctmm framework to
incorporate periodic patterns of space use. This does not require much modification of the ctmm …

… continuous-time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs
to infer the full movement … robust to model structure and variability in CTMM prediction. …

… , model selection techniques are employed to identify the best fit continuous-time movement
model for … To fit and select the movement, and error models, we use the R package ctmm, …

… now openly available via the ctmm R package. … continuous-time movement models to the
data, such as the Independent and Identically Distributed (IID), OU and OUF processes. Model …

… on the continuous-time Markov model (CTMM). To aid us in defining this type of model,
consider that Markov models can either be defined in discrete or continuous time. A discrete-time …

… model to discrete-time Markov model (DTMM) or standard continuous-time Markov model
(CTMM) for … data with Markov properties is presented: the minimal CTMM (mCTMM). Through a …

… Leveraging the ‘ctmm’ R package, we utilize two methods … estimators (AKDEs) and
continuous-time speed and distance (… by the data and the resulting movement model is fractal (ie …

… -state, continuous-time Markov model (CTMM) to profile sleep patterns of ageing adults
in the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study. By leveraging the CTMM to …