Get_C_R_K_Q | R Documentation |
This function computes the required values for the inverse covariance matrix.
Get_C_R_K_Q(index,GG,W,C0,VV)
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. |
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. |
A list of 4 items for C, R, K and Q.
Mengyang Gu [aut, cre], Xinyi Fang [aut], Yizi Lin [aut]
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.
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