Construct_G_exp: The coefficient matrix in the dynamic linear model when...
In FastGaSP: Fast and Exact Computation of Gaussian Stochastic Process
Description
Usage
Arguments
Value
Author(s)
References
Description
The coefficient matrix in the dynamic linear model when kernel is the exponential covariance.
Usage
1
Construct_G_exp(delta_x,lambda)
Arguments
delta_x
the distance between the sorted input.
lambda
the transformed range parameter.
Value
GG matrix.
Author(s)
Mengyang Gu [aut, cre]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>
References
Hartikainen, J. and Sarkka, S. (2010). Kalman filtering and smoothing solutions to temporal gaussian process regression models. Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop, 379-384.
M. Gu, Y. Xu (2019), fast nonseparable Gaussian stochastic process with application to methylation level interpolation. Journal of Computational and Graphical Statistics, In Press, arXiv:1711.11501.
Campagnoli P, Petris G, Petrone S. (2009), Dynamic linear model with R. Springer-Verlag New York.
FastGaSP documentation built on Sept. 5, 2021, 5:36 p.m.
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Description Usage Arguments Value Author(s) References
Description
The coefficient matrix in the dynamic linear model when kernel is the exponential covariance.
Usage
1 | Construct_G_exp(delta_x,lambda)
|
Arguments
delta_x |
the distance between the sorted input. |
lambda |
the transformed range parameter. |
Value
GG matrix.
Author(s)
Mengyang Gu [aut, cre]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>
References
Hartikainen, J. and Sarkka, S. (2010). Kalman filtering and smoothing solutions to temporal gaussian process regression models. Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop, 379-384.
M. Gu, Y. Xu (2019), fast nonseparable Gaussian stochastic process with application to methylation level interpolation. Journal of Computational and Graphical Statistics, In Press, arXiv:1711.11501.
Campagnoli P, Petris G, Petrone S. (2009), Dynamic linear model with R. Springer-Verlag New York.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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