Optimal estimation for semimartingale neuronal models
Tài liệu tham khảo
Basawa, 1980
Bellach, 1980, Consistency, asymptotic normality and asymptotic efficiency of the maximum-likelihood estimator in linear stochastic differential equations, Math. Operationsforsch. Statist. Ser. Statistics, 11, 227
Bellach, 1983, Parameter estimators in linear stochastic differential equations and their asymptotic properties, Math. Operationsforsch. Statist. Ser. Statistics, 14, 141
Brown, 1975, Asymptotic likelihood theory for diffusion processes, J. Appl. Probab., 12, 228, 10.2307/3212436
Christopeit, 1986, Quasi-least-squares estimation in semimartingale regression models, Stochastic, 16, 255, 10.1080/17442508608833376
Capocelli, 1971, Diffusion approximation and first passage time problem for a model neuron, Kybernetik, 8, 214, 10.1007/BF00288750
Elliot, 1982
Favella, 1982, First passage time problems and related computational models, Cybernet. Syst. Ser., 13, 95, 10.1080/01969728208927693
Feigin, 1976, Maximum likelihood estimation for continuous-time stochastic processes, Adv. in Appl. Probab., 8, 712, 10.2307/1425931
Ferster, 1987, Origin of orientation-selective EPSPs in neurons of cat visual cortex, J. Neurosci., 7, 1780, 10.1523/JNEUROSCI.07-06-01780.1987
Godambe, 1960, An optimum property of regular maximum likelihood equation, Ann. Math. Statist., 31, 1208, 10.1214/aoms/1177705693
Godambe, 1985, The foundations of finite sample estimation in stochastic processes, Biometrika, 12, 419, 10.1093/biomet/72.2.419
Godambe, 1987, Quasi-likelihood and optimal estimation, Internat. Statist. Rev., 55, 231, 10.2307/1403403
Habib, 1985, Parameter estimation for randomly stopped processes and neuronal modeling, UNC Institute of Statistics
Hall, 1980
Heyde, 1992, New developments in inference for temporal stochastic processes, J. Statist. Plann. Inference, 33, 121, 10.1016/0378-3758(92)90097-C
Hutten, 1986, Quasi-likelihood estimation for semimartingales, Stochastic Process. Appl., 22, 245, 10.1016/0304-4149(86)90004-9
Ikeda, 1981
Johannesma, 1968, Diffusion models for the stochastic activity of neurons
Kallianpur, 1983, On the diffusion approximation to a discontinuous model for a single neuron
Kandel, 1981
Lánský, 1983, Inference for the diffusion models of neuronal activity, Math. Biosci., 67, 247, 10.1016/0025-5564(83)90103-7
Lindsey, 1985, Using empirical partially Bayes inference for increased efficiency, Ann. Statist., 13, 914, 10.1214/aos/1176349646
Liptser, 1980, A functional central limit theorem for semi-martingales, Theory Probab. Appl., 25, 683
Liptser, 1981, On necessary and sufficient conditions on a central limit theorem for semi-martingales, Theory Prob. Appl., 25, 123
Ricciardi, 1976, Diffusion approximation for a multi-input model neuron, Biol. Cybernet., 24, 237, 10.1007/BF00335984
Ricciardi, 1979, The Örnstein–Uhlenbeck process as a model for neuronal activity, Biol. Cybernet., 35, 1, 10.1007/BF01845839
Shiryayev, 1981, Martingales: Recent developments, results and applications, Internat. Statist. Rev., 49, 199, 10.2307/1402605
Shiryayev, 1984
Snyder, 1975
Stein, 1965, Some models of neuronal variability, Biophys. J., 5, 173, 10.1016/S0006-3495(65)86709-1
Tanaka, 1983, Cross-correlation analysis of geniculostriate neuronal relationships in cats, J. Neurophysiol., 49, 1303, 10.1152/jn.1983.49.6.1303
Tuckwell, 1980, Accuracy of neuronal interspike times calculated from a diffusion approximation, J. Theoret. Biol., 83, 377, 10.1016/0022-5193(80)90045-4
Thavaneswaran, 1985, Estimation for Semimartingales
Thavaneswaran, 1986, Optimal estimation for semimartingales, J. Appl. Probab., 23, 409, 10.2307/3214183
Tjøstheim, 1986, Estimation in nonlinear time series models, Stochastic Process. Appl., 21, 251, 10.1016/0304-4149(86)90099-2
Wegman, 1990, Stochastic methods of neural systems, J. Statist. Plann. Inference, 33, 5, 10.1016/0378-3758(92)90092-7