The paper considers the statistical work of the physicist Harold Jeffreys. In 1933–4 Jeffreys had a controversy with R.A. Fisher, the leading statistician of the time. Prior to the encounter, Jeffreys had worked on probability as the basis for scientific inference and had used methods from the theory of errors in astronomy and seismology. He had also started to rework the theory of errors on th...

Entrevista a Sheila Jeffreys

In 1984, while tracking the veins of globin gene evolution and panning the human genome for hypervariable linkage markers, Sir Alec Jeffreys accidentally struck gold—he discovered a way to identify any human being by a DNA ‘‘fingerprint’’. To use Jeffreys’ words, he has been ‘‘branded’’ by DNA fingerprinting, but he delights in its application and the hook it provides for public curiosity about...

This paper addresses the use of Jeffreys priors in the context of univariate threeparameter location-scale models, where skewness is introduced by differing scale parameters either side of the location. We focus on various commonly used parameterizations for these models. Jeffreys priors are shown not to allow for posterior inference in the wide and practically relevant class of distributions o...

This paper introduces Jeffreys interval for one-sample proportion using SAS® software. It compares the credible interval from a Bayesian approach with the confidence interval from a frequentist approach. Different ways to calculate the Jeffreys interval are presented using PROC FREQ, the QUANTILE function, a SAS program of random walk Metropolis sampler, and PROC MCMC.

The problem of extending the Jeffreys-Matnsita distance to multiclass cases for feature-selection purposes is addressed and a solution equivalent to the Bhattacharyya bound is presented. This extension is compared with the widely used weighted average Jeffreys-Matusita distance both by examining the respective formulae and by experimenting on an optical remote-sensing data set.

We study the problem of data compression, gambling and prediction of a sequence x = x1x2...xn from a certain alphabet X , in terms of regret and redundancy with respect to a general exponential family. In particular, we evaluate the regret of the Bayes mixture density and show that it asymptotically achieves their minimax values when variants of Jeffreys prior are used. Keywords— universal codi...