Non‐Markovian maximum likelihood estimation of autocorrelated movement processes [PDF]
SummaryBy viewing animal movement paths as realizations of a continuous stochastic process, we introduce a rigorous likelihood method for estimating the statistical parameters of movement processes. This method makes no assumption of a hidden Markov property, places no special emphasis on the sampling rate, is insensitive to irregular sampling and data
Fleming, Christen H. +5 more
openaire +4 more sources
The Challenge of Time-to-Event Analysis for Multiple Events: A Guided Tour From Time-to-First-Event to Recurrent Time-to-Event Analysis. [PDF]
ABSTRACT Clinical trials often compare a treatment to a control group concerning multiple possible combined time‐to‐event endpoints like hospital‐free survival. Thereby, the first endpoint may occur more than once (“recurrent”), whereas the second endpoint is absorbing. Inclusion of all observed events in the analysis can increase the power and provide
Schmeller S +4 more
europepmc +2 more sources
Estimates for first exit times of non-Markovian Itô processes [PDF]
First exit times and their path-wise dependence on trajectories are studied for non-Markovian Ito processes. Estimates of distances between two exit times are obtained. In particular, it follows that first exit times of two Ito processes are close if their trajectories are close.
openaire +2 more sources
Bayesian inference of a spatially dependent semi-Markovian model with application to Madagascar Covid'19 data. [PDF]
Raherinirina A +3 more
europepmc +1 more source
Memory kernel minimization-based neural networks for discovering slow collective variables of biomolecular dynamics. [PDF]
Liu B, Cao S, Boysen JG, Xue M, Huang X.
europepmc +1 more source
Quantifying local stability and noise levels from time series in the US Western Interconnection blackout on 10th August 1996. [PDF]
Heßler M, Kamps O.
europepmc +1 more source
Optimized Fractional-Order Extended Kalman Filtering for IMU-Based Attitude Estimation Using the Hippopotamus Algorithm. [PDF]
Yang X +5 more
europepmc +1 more source
Fast and exact stochastic simulations of epidemics on static and temporal networks. [PDF]
Cure S, Pflug FG, Pigolotti S.
europepmc +1 more source
Genome sequencing uncovers the history of the Russian desman's gradual population decline and contributes to the evolutionary history of Talpidae. [PDF]
Kosushkin SA +8 more
europepmc +1 more source

