Examples comparing importance sampling and the Metropolis algorithm
Bassetti, Federico ; Diaconis, Persi
Illinois J. Math., Tome 50 (2006) no. 1-4, p. 67-91 / Harvested from Project Euclid
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Importance sampling, particularly sequential and adaptive importance sampling, have emerged as competitive simulation techniques to Markov-chain Monte-Carlo techniques. We compare importance sampling and the Metropolis algorithm as two ways of changing the output of a Markov chain to get a different stationary distribution.
Publié le : 2006-05-15
Classification:  60J10,  65C05 
@article{1258059470,
     author = {Bassetti, Federico and Diaconis, Persi},
     title = {Examples comparing importance sampling and the Metropolis algorithm},
     journal = {Illinois J. Math.},
     volume = {50},
     number = {1-4},
     year = {2006},
     pages = { 67-91},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1258059470}
}

Bassetti, Federico; Diaconis, Persi. Examples comparing importance sampling and the Metropolis algorithm. Illinois J. Math., Tome 50 (2006) no. 1-4, pp.  67-91. http://gdmltest.u-ga.fr/item/1258059470/