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arXiv · 1904.05849

KLTS: A rigorous method to compute the confidence intervals for the Three-Cornered Hat and for Groslambert Covariance

Éric Lantz·Claudio E. Calosso·Enrico Rubiola·Vincent Giordano·Christophe Fluhr·Benoît Dubois·François Vernotte
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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-Loève 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.

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Éric Lantz, Claudio E. Calosso, Enrico Rubiola, Vincent Giordano, Christophe Fluhr, Benoît Dubois, François Vernotte. 2019-08-01. KLTS: A rigorous method to compute the confidence intervals for the Three-Cornered Hat and for Groslambert Covariance. https://arxiv.org/abs/1904.05849

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