Hi,
I'm new to MCMC sampling techniques. Can someone give me pointers on how I would use pymc3 to model a mixture of gaussians ?
Something like:
y = (p) * N(mean1,sigma1) + (1-p)*N(mean2, sigma2) ?
And how to generalize to any number of gaussians?
Thanks,
Winnie
Hi Winnie,
We don't currently support pymc3, but it may be possible to add it to the modules we support. Do you want me to look into adding this module to Quantopian?
You can also do this with numpy, if I'm understanding you correctly. See here. I think you could create an MC sample for different gaussians, then superimpose the samples together and sample from that distribution. There probably some other good approaches, too.
Gus
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In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
