madsjulia / affineinvariantmcmc.jl Goto Github PK
View Code? Open in Web Editor NEWAffine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler
Home Page: http://mads.gitlab.io
License: Other
Affine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler
Home Page: http://mads.gitlab.io
License: Other
This issue is used to trigger TagBot; feel free to unsubscribe.
If you haven't already, you should update your TagBot.yml
to include issue comment triggers.
Please see this post on Discourse for instructions and more details.
If you'd like for me to do this for you, comment TagBot fix
on this issue.
I'll open a PR within a few hours, please be patient!
Good day,
Thank you so much for making this library.
I am relatively new to Julia in general and trying to port over an MCMC tool I wrote in python with emcee. I have successfully gotten it working with your library (and it's loads faster - which was my purpose for porting, so quite happy!)
I need to pass additional arguments to my llhood function outside of the vector with the parameters. (I have a bunch of details that are required to run the function, that do not change during sampling.) In emcee this is trivial (you can pass an args argument, ie:
sampler = emcee.EnsembleSampler(nwalkers, ndim, logpost, args=[case])
) but I do not see how to do that in this library. (For testing, I just hard coded the details in the function...)
I tried modifying the sample function to pass more to the rpmap call, I made a bit of progress but it was too complicated for me.
Is there an obvious way I'm missing here? Or any other suggestions?
Thank you!
It would be useful to add an acceptance rate to the sampler to see whether the a
parameter should be adjusted.
If the acceptance rate is too small, I would adjust the a
parameter closer to unity automatically via:
a_{new} = 1 + (a_{old} -1)*(acc_{measured}/acc_{target})
where acc_{measured}
is the measured value of acceptance (over some number of steps), while acc_{target}
is a target acceptance rate (usually 25%). Then, once the target acceptance rate is reached, the value of a
stays constant.
I like how easy it is to sample in parallel with the emcee python package (just set the threads keyword to >1). Do you have any plans to implement this in a similar fashion?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.