Maximum likelihood estimations in a nonlinear self-exciting point process model

DOI10.1007/BF00355597zbMath0623.62080OpenAlexW2120525066WikidataQ52650924 ScholiaQ52650924MaRDI QIDQ1091726

Henk F. P. van den Boogaard

Publication date: 1986

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00355597

zbMATH Keywords

nonlinear modelmaximum likelihood estimationsself-exciting point processcorrelation densitiessimultaneous recordings of single unitswiring diagrams

Mathematics Subject Classification ID

Non-Markovian processes: estimation (62M09) Identification in stochastic control theory (93E12) Inference from stochastic processes (62M99)

Related Items (5)

Maximum likelihood analysis of spike trains of interacting nerve cells ⋮ System identification based on point processes and correlation densities. II. The refractory neuron model ⋮ Maximum likelihood identification of neural point process systems ⋮ Minimum mean square error estimation of connectivity in biological neural networks ⋮ Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity

Cites Work

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• Maximum likelihood estimation of Hawkes' self-exciting point processes
• Stochastic formulation of neural interaction
• Identification of synaptic interactions
• The identification of point process systems
• System identification based on point processes and correlation densities. I: The nonrefractory neuron model
• Spectra of some self-exciting and mutually exciting point processes

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