Bayesian Modeling with R and Stan (Reupload)
Recent advances in Markov Chain Monte Carlo (MCMC) simulation have led to the development of a high-level probability modeling language called Stan. In this presentation, Sean Raleigh will give a gentle introduction to Bayesian inference using R and Stan.
Sean Raleigh received his Ph.D. in mathematics from U.C. San Diego, specializing in geometric topology and knot theory. He is a professor of mathematics at Westminster College and currently chairs the data science program. As part of Sean's professional work, he advocates for Bayesian methods in data analysis and co-directs QUARC, the Quantitative Analysis and Research Cooperative.
Видео Bayesian Modeling with R and Stan (Reupload) канала Salt Lake City R Users Group
Sean Raleigh received his Ph.D. in mathematics from U.C. San Diego, specializing in geometric topology and knot theory. He is a professor of mathematics at Westminster College and currently chairs the data science program. As part of Sean's professional work, he advocates for Bayesian methods in data analysis and co-directs QUARC, the Quantitative Analysis and Research Cooperative.
Видео Bayesian Modeling with R and Stan (Reupload) канала Salt Lake City R Users Group
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15 ноября 2018 г. 23:13:19
00:52:47
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