Maximum likelihood estimation for doubly stochastic poisson processes with partial observations

DOI10.1080/17442508608833366zbMath0585.62145OpenAlexW2093566354MaRDI QIDQ3709702

Franz Konecny

Publication date: 1986

Published in: Stochastics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17442508608833366

zbMATH Keywords

consistencyasymptotic normalityasymptotic efficiencypoint processesGirsanov theoremZakai equationdoubly stochastic Poisson processpoint process filteringergodic caseconvergence of the momentsconditional likelihood ratiointensity parameter estimationnonlinear filtering approachunobservable diffusion process

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Filtering in stochastic control theory (93E11) Markov processes: estimation; hidden Markov models (62M05) Asymptotic properties of parametric tests (62F05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (1)

Estimation and filtering on a doubly stochastic poisson process

Cites Work

• Unnamed Item
• The asymptotic behaviour of maximum likelihood estimators for stationary point processes
• On Discontinuous Martingales

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