38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
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# (mostly translation, see implementation details)
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# License: BSD style
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"""
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A module that implements scalar Gaussian Process based prediction (also
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known as Kriging).
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Contains
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--------
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GaussianProcess: The main class of the module that implements the Gaussian
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Process prediction theory.
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regression_models: A submodule that contains the built-in regression models.
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correlation_models: A submodule that contains the built-in correlation models.
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Implementation details
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----------------------
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The presentation implementation is based on a translation of the DACE
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Matlab toolbox, see reference [1].
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References
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----------
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[1] H.B. Nielsen, S.N. Lophaven, H. B. Nielsen and J. Sondergaard (2002).
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DACE - A MATLAB Kriging Toolbox.
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http://www2.imm.dtu.dk/~hbn/dace/dace.pdf
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[2] W.J. Welch, R.J. Buck, J. Sacks, H.P. Wynn, T.J. Mitchell, and M.D.
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Morris (1992). Screening, predicting, and computer experiments.
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Technometrics, 34(1) 15--25.
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"""
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from .gaussian_process import GaussianProcess
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from . import correlation_models
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from . import regression_models
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