The conditional covariance matrix of the state in the dynamic linear model when kernel is the exponential covariance.
Construct_W_exp(sigma2,delta_x,lambda,W0)W matrix.
the variance parameter.
the distance between the sorted input.
the transformed range parameter.
the covariance matrix of the stationary distribution of the state.
tools:::Rd_package_author("FastGaSP")
Maintainer: tools:::Rd_package_maintainer("FastGaSP")
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.