English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Group-based social dominance hierarchies are of essential interest in animalbehavior research. Studies often record aggressive interactions observed overtime, and models that can capture such dynamic hierarchy are therefore crucial.Traditional ranking methods summarize interactions across time, using onlyaggregate counts. Instead, we take advantage of the interaction timestamps,proposing a series of network point process models with latent ranks. Wecarefully design these models to incorporate important characteristics ofanimal interaction data, including the winner effect, bursting and pair-flipphenomena. Through iteratively constructing and evaluating these models wearrive at the final cohort Markov-Modulated Hawkes process (C-MMHP), which bestcharacterizes all aforementioned patterns observed in interaction data. Wecompare all models using simulated and real data. Using statistically developeddiagnostic perspectives, we demonstrate that the C-MMHP model outperforms othermethods, capturing relevant latent ranking structures that lead to meaningfulpredictions for real data.

Network Hawkes Process Models for Exploring Latent Hierarchy in Social Animal Interactions