https://github.com/tmcclintock/gpsampler
Given a likelihood function and an array of parameters, we can construct a latin-hypercube in the parameter space from which we can build a Gaussian process to make predictions of that function.
https://github.com/tmcclintock/gpsampler
Last synced: about 2 months ago
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Given a likelihood function and an array of parameters, we can construct a latin-hypercube in the parameter space from which we can build a Gaussian process to make predictions of that function.
- Host: GitHub
- URL: https://github.com/tmcclintock/gpsampler
- Owner: tmcclintock
- License: mit
- Created: 2017-08-02T14:26:31.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2017-08-02T18:07:33.000Z (almost 8 years ago)
- Last Synced: 2025-02-07T16:36:19.639Z (3 months ago)
- Language: Python
- Size: 3.91 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# GPSampler
Given a likelihood function and an array of parameters, we can construct a latin-hypercube in the parameter space from which we can build a Gaussian process to make predictions of that function.