FastGaSP (version 0.5.2)

Get_C_R_K_Q: matrices and vectors for the inverse covariance in the predictive distribution

Description

This function computes the required values for the inverse covariance matrix.

Usage

Get_C_R_K_Q(index,GG,W,C0,VV)

Arguments

index

a vector of integer of 0 and 1. 0 means no observation at that input and 1 means there is observations at that input.

have_noise

a bool value. If it is true, it means the model contains a noise.

GG

a list of matrices defined in the dynamic linear model.

W

a list of matrices defined in the dynamic linear model.

C0

a matrix defined in the dynamic linear model.

VV

a numerical value for the nugget.

Value

A list of 4 items for C, R, K and Q.

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.