Confidence Intervals for Three-Cornered Hat and Groslambert Covariance Estimates

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 method which takes into account all the measurements between the pairs of clocks in a Bayesian way. The result is the Cumulative Density Function which yields confidence intervals for each clock AVAR. This CDF provides also a stability estimator which is always positive.Checked by massive Monte-Carlo simulations, this method proves to be perfectly reliable even for two degrees of freedom.