February 21, 2012 7:00 PM - 35 attended
Bayesian statistics in R
This talk will be a basic introduction to Bayesian estimation through a serious of illustrations with a linear modelling problem. In particular, a little of the mathematics and a lot of the estimation behind the Metropolis-Hastings algorithm and Gibbs sampling (the two most common Bayesian estimation methodologies) will be compared to OLS and maximum likelihood (two common frequentist approaches).
Ben Domingue is currently finishing a PhD at CU-Boulder in the School of Education. He has worked in a variety of fields including psychometrics, value-added and growth modeling, genome-wide studies, and social network analysis.
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Emilija Nikolic-Djoric
I am very interested in Bayesian estimation but I can't be present as I am so far (Serbia). I thought that it is webinar.
Best regards!Posted February 16 at 11:56 PM -
Steven Matthew Anderson
A webinar would awesome! What does it take set on up?
Posted February 17 at 1:33 AM -
Paul Geissler
I have a 15 user license for GoToMeeting that we could use.
AnyMeeting (http://www.anymeeting.com/
) is a free alternative, but I have not as good lick with it.Posted February 17 at 1:30 PM -
Bart Kastermans
When I put a post on google+ that I was coming to this meetup I got a comment with lots of other Bayesian talks, figured I should share here:
https://plus.google.com/102085185756507251350/posts/Btb6GX...Posted Tuesday at 9:35 PM
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RichardThe content had at best 4 slides on R. There were zero applied use cases. The focus was on math, while the title online Implied a 'gentle' approach. I drove 45 minutes Expecting something R focused and instead Got a grad level stas dissertation with poor r. A complete waste of my time. Lastly, you started over twenty minutes late
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Provides funding to this meetup group
from Revolution Analytics
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