Construct_W_matern_5_2: The conditional covariance matrix for matern covariance with...
In FastGaSP: Fast and Exact Computation of Gaussian Stochastic Process

Description Usage Arguments Value Author(s) References

The conditional covariance matrix of the state in the dynamic linear model when kernel is the matern covariance with roughness parameter 2.5.

1	Construct_W_matern_5_2(sigma2,delta_x,lambda,W0)

`sigma2`	the variance parameter.
`delta_x`	the distance between the sorted input.
`lambda`	the transformed range parameter.
`W0`	the covariance matrix of the stationary distribution of the state.

W matrix.

Mengyang Gu [aut, cre]

Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>

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.