Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations
DOI10.1162/neco_a_01121zbMath1472.92075DBLPjournals/neco/RuleS18arXiv1801.00475OpenAlexW3099023707WikidataQ91156999 ScholiaQ91156999MaRDI QIDQ5157255
Guido Sanguinetti, Michael Rule
Publication date: 12 October 2021
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1801.00475
spike train dataautoregressive point-process generalized linear modelslatent state-space models with point-process observations
Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)
Uses Software
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