Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering-Reference-Cited by-同舟云学术

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Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering

Published:2012-08-03 Issue:3 Volume:28 Page:1195-1223
ISSN:0943-4062
Container-title:Computational Statistics
language:en
Short-container-title:Comput Stat

Author:

Mbalawata Isambi S.,Särkkä Simo,Haario Heikki

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s00180-012-0352-y.pdf

Reference54 articles.

1. Aït-Sahalia Y (2002) Maximum likelihood estimation of discretely sampled diffusions: a closed-form approximation approach. Econometrica 70(1):223–262

2. Aït-Sahalia Y (2008) Closed-form expansion for multivariate diffusions. Ann Stat 36(2):906–937

3. Andrieu C, Thoms J (2008) A tutorial on adaptive MCMC. Stat Comput 18(4):343–373

4. Andrieu C, Doucet A, Holenstein R (2010) Particle Markov chain Monte Carlo methods. R Stat Soc Ser B Stat Methodol 72(3):269–342

5. Berg EVD, Heemink AW, Lin HX, Schoenmakers J (2006) Probability density estimation in stochastic environmental models using reverse representations. Stoch Environ Res Risk Assess 20(1–2):126–139

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