Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)
Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)
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DOI：
10.1111/j.1467-9868.2006.00552.x
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发表时间：
2006-01-01
影响因子：
5.8
通讯作者：
Fearnhead, Paul
中科院分区：
文献类型：
--
作者：
Beskos, Alexandros;Papaspiliopoulos, Omiros;Fearnhead, Paul
本文的目的是提出一种新颖的方法，用于离散观察扩散的基于可能性的推理。我们提出了蒙特卡罗方法，该方法建立在扩散精确模拟的最新进展之上，用于执行最大似然和贝叶斯估计。
The objective of the paper is to present a novel methodology for likelihood-based inference for discretely observed diffusions. We propose Monte Carlo methods, which build on recent advances on the exact simulation of diffusions, for performing maximum likelihood and Bayesian estimation.