Bayesian estimation with Markov Chain Monte Carlo using PyMC – New York R Statistical Programming Meetup

by cp2530 on November 1, 2010

Title: Bayesian estimation with Markov Chain Monte Carlo using PyMC – New York R Statistical Programming Meetup
Location: International Affairs Building, Room 707, 420 W. 118th St
Link out: Click here
Description: Speaker:
Chris Fonnesbeck, Department of Biostatistics, Vanderbilt University

Chris is one of the co-creators of PyMC, the premier package for MCMC estimation in Python. From PyMC’s website:

Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. PyMC is a python module that implements the Metropolis-Hastings algorithm as a python class, and is extremely flexible and applicable to a large suite of problems. PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.

RSVP on the meetup website!
Start Time: 18:15
Date: 2010-11-03

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