123 citations · 282 across the 10 of their papers we have counts for
12 papers
A primer on coupled state-switching models for multiple interacting time series
Jennifer Pohle, Roland Langrock, Mihaela van der Schaar +2
State-switching models such as hidden Markov models or Markov-switching regression models are routinely applied to analyse sequences of observations that are driven by underlying n…
Parameter clustering in Bayesian functional PCA of fMRI data
Nicolo' Margaritella, Vanda Inacio, Ruth King
The extraordinary advancements in neuroscientific technology for brain recordings over the last decades have led to increasingly complex spatio-temporal datasets. To reduce oversim…
Parameter Redundancy and the Existence of Maximum Likelihood Estimates in Log-linear Models
Serveh Sharifi Far, Michail Papathomas, Ruth King
Log-linear models are typically fitted to contingency table data to describe and identify the relationship between different categorical variables. However, the data may include ob…
Estimating abundance from multiple sampling capture-recapture data via a multi-state multi-period stopover model
Hannah Worthington, Rachel McCrea, Ruth King +1
The collection of capture-recapture data often involves collecting data on numerous capture occasions over a relatively short period of time. For many study species this process is…
Estimation of population size when capture probability depends on individual states
Hannah Worthington, Rachel S. McCrea, Ruth King +1
We develop a multi-state model to estimate the size of a closed population from ecological capture-recapture studies. We consider the case where capture-recapture data are not of a…
Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges
Toby A Patterson, Alison Parton, Roland Langrock +3
With the influx of complex and detailed tracking data gathered from electronic tracking devices, the analysis of animal movement data has recently emerged as a cottage industry amo…
Capture-recapture abundance estimation using a semi-complete data likelihood approach
Ruth King, Brett T. McClintock, Darren Kidney +1
Capture-recapture data are often collected when abundance estimation is of interest. In the presence of unobserved individual heterogeneity, specified on a continuous scale for the…
Semi-Markov Arnason-Schwarz models
Ruth King, Roland Langrock
We consider multi-state capture-recapture-recovery data where observed individuals are recorded in a set of possible discrete states. Traditionally, the Arnason-Schwarz model has b…
Maximum penalized likelihood estimation in semiparametric capture-recapture models
Théo Michelot, Roland Langrock, Thomas Kneib +1
We discuss the semiparametric modeling of mark-recapture-recovery data where the temporal and/or individual variation of model parameters is explained via covariates. Typically, in…
Modelling group dynamic animal movement
Roland Langrock, J. Grant C. Hopcraft, Paul G. Blackwell +7
Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, part…
Maximum likelihood estimation of mark-recapture-recovery models in the presence of continuous covariates
Roland Langrock, Ruth King
We consider mark-recapture-recovery (MRR) data of animals where the model parameters are a function of individual time-varying continuous covariates. For such covariates, the covar…
Importance Tempering
Robert B. Gramacy, Richard J. Samworth, Ruth King
Simulated tempering (ST) is an established Markov chain Monte Carlo (MCMC) method for sampling from a multimodal density . Typically, ST involves introducing an auxiliary var…