Maximum likelihood identification of neural point process systems
DOI10.1007/BF00332915zbMath0658.92007OpenAlexW2075618168WikidataQ52580103 ScholiaQ52580103MaRDI QIDQ1111960
E. S. Chornoboy, L. P. Schramm, Alan F. Karr
Publication date: 1988
Published in: Biological Cybernetics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf00332915
algorithmmaximum likelihood estimatesstochastic intensityConvergence resultsadditive risk modelfunctional relationships between two neuronsiterative solution of the likelihood equations
Inference from stochastic processes (62M99) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Physiological, cellular and medical topics (92Cxx)
Related Items (49)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A new statistical method for identifying interconnections between neuronal network elements
- Maximum likelihood estimations in a nonlinear self-exciting point process model
- Maximum likelihood estimation in the multiplicative intensity model via sieves
- The asymptotic behaviour of maximum likelihood estimators for stationary point processes
- The identification of point process systems
- Nonparametric inference for a family of counting processes
- An algorithm for maximizing expected log investment return
- The numerical evaluation of the maximum-likelihood estimate of mixture proportions
- A Statistical Model for Positron Emission Tomography
- Spectra of some self-exciting and mutually exciting point processes
This page was built for publication: Maximum likelihood identification of neural point process systems