Method of moments estimators and multi-step MLE for Poisson processes
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Publication:1616201
DOI10.3103/S1068362318040064zbMath1404.62025arXiv1806.06378OpenAlexW2964331365MaRDI QIDQ1616201
A. A. Gounoung, Ali Souleymane Dabye, Yury A. Kutoyants
Publication date: 1 November 2018
Published in: Journal of Contemporary Mathematical Analysis. Armenian Academy of Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.06378
consistencyasymptotic normalityasymptotic efficiencyinhomogeneous Poisson processmethod of moments estimatormulti-step MLE
Asymptotic properties of parametric estimators (62F12) Point estimation (62F10) Markov processes: estimation; hidden Markov models (62M05)
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Cites Work
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- On multi-step MLE-process for Markov sequences
- Adaptive estimation of an ergodic diffusion process based on sampled data
- Approximation of the solution of the backward stochastic differential equation. Small noise, large sample and high frequency cases
- Statistical inference for spatial Poisson processes
- On parameter estimation of hidden telegraph process
- On approximation of BSDE and multi-step MLE-processes
- Hybrid multi-step estimators for stochastic differential equations based on sampled data
- On the multi-step MLE-process for ergodic diffusion
- The Stochastic Difference Between Econometric Statistics
- Testing the hypothesis that a point is Poisson
- Communication under the Poisson regime