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목록particle filter (1)
CHOU
パーティクルフィルタ
Particle filters, also known as sequential Monte Carlo methods (SMC), are sophisticated model estimation techniques based on simulation. Particle filters have important applications in econometrics[1]. They are usually used to estimate Bayesian models and are the sequential ('on-line') analogue of Markov chain Monte Carlo (MCMC) batch methods and are often similar to importance sampling methods...
Tech/Technical Tips
2010. 4. 21. 23:37