[
{
"url": "https://link.springer.com/chapter/10.1007/978-3-7908-2628-9_7",
"itemType": "bookSection",
"place": "Heidelberg",
"publisher": "Physica-Verlag HD",
"pages": "97–111",
"title": "On Implementation of the Markov Chain Monte Carlo Stochastic Approximation Algorithm",
"bookTitle": "Advances in Directional and Linear Statistics",
"date": "2010-09-27",
"ISBN": [ "9783790826272", "9783790826289"],
"language": "en",
"abstractNote": "The Markov Chain Monte Carlo Stochastic Approximation Algorithm (MCMCSAA) was developed to compute estimates of parameters with incomplete data. In theory this algorithm guarantees convergence to the...",
"accessDate": "2018-10-09",
"author": [
["Yihua", "Jiang"],
["Peter", "Karcher"],
["Yuedong", "Wang"]
],
"DOI": "10.1007/978-3-7908-2628-9_7",
"source": [ "Crossref", "citoid"]
}
]
Jiang, Y., Karcher, P., & Wang, Y. (2010). "On Implementation of the Markov Chain Monte Carlo Stochastic Approximation Algorithm." Advances in Directional and Linear Statistics edited by Martin T. Wells. Physica-Verlag HD, pp. 97–111.
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https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002947