get_LY_online: Updating Kalman filter parameters

View source: R/RcppExports.R

get_LY_onlineR Documentation

Updating Kalman filter parameters

Description

Updating the Kalman filter parameters for Gaussian Process model with Matern 2.5 or power exponential kernels.

Usage

  get_LY_online(cur_input, prev_param, eta, G_W_W0_V)

Arguments

cur_input

A value of current observation.

prev_param

A list of previous Kalman filter parameters.

eta

The noise-to-signal ratio.

G_W_W0_V

A list of the coefficient and conditional matrics for Gaussian Process(GP) model. It's the output from the function Construct_G_W_W0_V

Value

get_LY_online returns a list of updated kalman filter parameters.

Author(s)

Hanmo Li [aut, cre], Yuedong Wang [aut], Mengyang Gu [aut]

Maintainer: Hanmo Li <hanmo@pstat.ucsb.edu>

References

Fearnhead, P., & Liu, Z. (2007). On-line inference for multiple changepoint problem. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 69(4), 589-605.

Adams, R. P., & MacKay, D. J. (2007). Bayesian online changepoint detection. arXiv preprint arXiv:0710.3742.

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.


SKFCPD documentation built on June 22, 2024, 11:06 a.m.