Joint non-parametric estimation of mean and auto-covariances for Gaussian processes

Krivobokova T.; Serra P.; Rosales F.; Klockmann K. · Computational Statistics and Data Analysis (2022) · DOI: 10.1016/j.csda.2022.107519

Resumen

Gaussian processes that can be decomposed into a smooth mean function and a stationary autocorrelated noise process are considered and a fully automatic nonparametric method to simultaneous estimation of mean and auto-covariance functions of such processes is developed. The proposed empirical Bayes approach is data-driven, numerically efficient, and allows for the construction of confidence sets for the mean function. Performance is demonstrated in simulations and real data analysis. The method is implemented in the R package eBsc.1

Instituciones: Universidad ESAN