KLTS: A rigorous method to compute the confidence intervals for the Three-Cornered Hat and for Groslambert Covariance
Abstract
The three-cornered hat / Groslambert Covariance methods are widely used to estimate the stability of each individual clock in a set of three, but no method gives reliable confidence intervals for large integration times. We propose a new KLTS (Karhunen-Lo\`eve Tansform using Sufficient statistics) method which uses these estimators to take into account the statistics of all the measurements between the pairs of clocks in a Bayesian way. The resulting Cumulative Density Function (CDF) yields confidence intervals for each clock AVAR. This CDF provides also a stability estimator which is always positive. Checked by massive Monte-Carlo simulations, KLTS proves to be perfectly reliable even for one degree of freedom. An example of experimental measurement is given.
Keywords
Cite
@article{arxiv.1904.05849,
title = {KLTS: A rigorous method to compute the confidence intervals for the Three-Cornered Hat and for Groslambert Covariance},
author = {Éric Lantz and Claudio E. Calosso and Enrico Rubiola and Vincent Giordano and Christophe Fluhr and Benoît Dubois and François Vernotte},
journal= {arXiv preprint arXiv:1904.05849},
year = {2019}
}
Comments
7 pages, 5 figures