Last Tuesday we got together for the 4th <a href="http://meetup.com/Bayesian-Mixer-London/">Bayesian Mixer Meetup</a>. <a href="http://www.productmadness.com/">Product Madness</a> kindly hosted us at their offices in Euston Square. About 50 Bayesians came along; the biggest turn up thus far, including developers of <a href="https://github.com/pymc-devs/pymc3">PyMC3</a> (<a href="https://peadarcoyle.wordpress.com/">Peadar Coyle</a>) and <a href="https://www.blogger.com/mc-stan.org">Stan</a> (<a href="http://betanalpha.github.io/">Michael Betancourt</a>).<br><br>The agenda had two feature talks by <a href="https://idontgetoutmuch.wordpress.com/about/">Dominic Steinitz</a> and <a href="https://www.linkedin.com/in/volodymyr-kazantsev-3307321">Volodymyr Kazantsev</a> and a lightning talk by <a href="http://blog.applied.ai/author/jonathan-sedar/">Jon Sedar</a>.<br><br><table align="center" cellpadding="0" cellspacing="0"><tr><td><a href="https://3.bp.blogspot.com/-dPWq-8GhzyU/V_NA-oMIioI/AAAAAAAACnU/2JCAkpgc3JACanRqggzFxhkCHDh-9WbJQCLcB/s1600/IMG_0658.jpg"></a></td></tr><tr><td>Dominic Steinitz: <a href="http://files.meetup.com/19578779/Dominic%20Steinitz%20Hamiltonian%20and%20Sequential%20Monte%20Carlo%20An%20Ecosy.pdf">Hamiltonian and Sequential MC samplers to model ecosystems</a></td></tr></table>Dominic shared with us his experience of using <a href="http://files.meetup.com/19578779/Dominic%20Steinitz%20Hamiltonian%20and%20Sequential%20Monte%20Carlo%20An%20Ecosy.pdf">Hamiltonian and Sequential Monte Carlo samplers to model ecosystems</a>. <br><br><table align="center" cellpadding="0" cellspacing="0"><tr><td><a href="https://2.bp.blogspot.com/-LfDkZ51hBZ4/V_NA-pmGXeI/AAAAAAAACnQ/Lkf6PjcQTnEyX6yNe3iMezzGeoxWJeeoQCLcB/s1600/IMG_0660.jpg"></a></td></tr><tr><td>Volodymyr Kazantsev: <a target="_blank" href="http://www.slideshare.net/vladimirkazantsev/bayesian-model-averaging">Bayesian Model Averaging</a></td></tr></table>Finding the 'best' model was <a href="http://www.slideshare.net/vladimirkazantsev/bayesian-model-averaging">Volodymyr's challenge</a>. He tried various R packages (<a href="https://cran.r-project.org/package=BMA">BMA</a>, <a href="https://cran.r-project.org/package=BMS">BMS</a> and <a href="https://cran.r-project.org/package=BAS">BAS</a>) for Bayesian model averaging, with various degrees of success. <br><br><table align="center" cellpadding="0" cellspacing="0"><tr><td><a href="https://4.bp.blogspot.com/-qbbqlMlwNTU/V_NA-mhQ_II/AAAAAAAACnM/1YdyLPn9hqoglG-565c_TrVErrkJ7OhwgCLcB/s1600/IMG_0661.jpg"></a></td></tr><tr><td>Jon Sedar: <a target="_blank" href="http://blog.applied.ai/easier-plate-notation-in-python-using-daft/">Easier Plate Notation in Python using Daft</a></td></tr></table>Finally, Jon gave a brief overview on <a href="http://blog.applied.ai/easier-plate-notation-in-python-using-daft/">Daft</a>, a nifty Python package for creating graphs, or plate notation.<br><h3>Next meeting</h3>The next <a href="http://www.meetup.com/Bayesian-Mixer-London/events/233887662/">Bayesian Mixer Meetup</a> meeting is already scheduled for 21 October. We will be back at Cass Business School, with two talks:<br><br><ul><li>Darren Wilkinson: Hierarchical Bayesian Modelling of Growth Curves inc Stochastic Processes</li><li>Peadar Coyle: Advanced PyMC3</li></ul><div>This post was originally published on <a href="http://www.magesblog.com/">mages’ blog</a>.</div>