#Particle Learning Models
ParticleLearningModels provides Java code for Bayesian particle filters with parameter learning. Parameter learning is implemented as in [Carvalho, et. al.][pl1], [Lopes, et. al.][pl2], [Carvalho, et. al][pl3], and the forthcoming [Polson, Willard][rbc1].
This library uses StatsLibExtensions and is used by the R package ParticleBayes
The javadoc is hosted here.
[pl1]:http://projecteuclid.org/euclid.ss/1280841735 "Carvalho, Carlos M., Michael S. Johannes, Hedibert F. Lopes, and Nicholas G. Polson. "Particle learning and smoothing." Statistical Science 25, no. 1 (2010): 88-106." [pl2]:http://www2.mccombs.utexas.edu/faculty/carlos.carvalho/LopesV9chapter.pdf "Lopes, Hedibert F., Carlos M. Carvalho, Michael Johannes, and Nicholas G. Polson. "Particle learning for sequential Bayesian computation." Bayesian Statistics 9 (2010): 2010." [pl3]:http://projecteuclid.org/euclid.ba/1340110852 "Carvalho, Carlos M., Hedibert F. Lopes, Nicholas G. Polson, and Matt A. Taddy. "Particle learning for general mixtures." Bayesian Analysis 5, no. 4 (2010): 709-740." [rbc1]: "Nicholas G. Polson and Brandon T. Willard. "Recursive Bayesian Computation""