Construct_W_exp: The conditional covariance matrix of the state in the dynamic...

View source: R/RcppExports.R

Construct_W_expR Documentation

The conditional covariance matrix of the state in the dynamic linear model when kernel is the exponential covariance

Description

The conditional covariance matrix of the state in the dynamic linear model when kernel is the exponential covariance.

Usage

Construct_W_exp(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]

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

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 May 29, 2024, 1:30 a.m.