Construct_W_matern_5_2: The conditional covariance matrix for matern covariance with...

In FastGaSP: Fast and Exact Computation of Gaussian Stochastic Process

The conditional covariance matrix for matern covariance with roughness parameter 2.5

Description

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

Usage

Construct_W_matern_5_2(sigma2,delta_x,lambda,W0)

Arguments

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.

Value

W matrix.

Author(s)

Mengyang Gu [aut, cre], Xinyi Fang [aut], Yizi Lin [aut]

Maintainer: Mengyang Gu <[e-mail]>

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 April 4, 2025, 5:16 a.m.