Analytic posteriors for Pearson's correlation coefficient

Pearson's correlation is one of the most common measures of linear dependence. Recently, Bernardo (11th International Workshop on Objective Bayes Methodology, 2015) introduced a flexible class of priors to study this measure in a Bayesian setting. For this large class of priors, we show that the (marginal) posterior for Pearson's correlation coefficient and all of the posterior moments are analytic. Our results are available in the open‐source software package JASP.

[1]  R. Fisher A mathematical Examination of the Methods of determining the Accuracy of Observation by the Mean Error, and by the Mean Square Error , 1920 .

[2]  R. Fisher,et al.  On the Mathematical Foundations of Theoretical Statistics , 1922 .

[3]  James O. Berger,et al.  Objective Bayesian Analysis for the Multivariate Normal Model , 2006 .

[4]  L. Tierney Markov Chains for Exploring Posterior Distributions , 1994 .

[5]  David Lindley,et al.  Introduction to Probability and Statistics from a Bayesian Viewpoint , 1966 .

[6]  M. Stone,et al.  Marginalization Paradoxes in Bayesian and Structural Inference , 1973 .

[7]  Edmund Taylor Whittaker On the Functions associated with the Parabolic Cylinder in Harmonic Analysis , 1902 .

[8]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

[9]  Jan Hannig,et al.  Fiducial Inference , 2011, International Encyclopedia of Statistical Science.

[10]  R. Fisher 014: On the "Probable Error" of a Coefficient of Correlation Deduced from a Small Sample. , 1921 .

[11]  C. Robert,et al.  Harold Jeffreys’s Theory of Probability Revisited , 2008, 0804.3173.

[12]  L. Debnath Tables of Integral Transforms , 2012 .

[13]  R. Fisher FREQUENCY DISTRIBUTION OF THE VALUES OF THE CORRELATION COEFFIENTS IN SAMPLES FROM AN INDEFINITELY LARGE POPU;ATION , 1915 .

[14]  H. Jeffreys,et al.  The Theory of Probability , 1896 .

[15]  H. Jeffreys Some Tests of Significance, Treated by the Theory of Probability , 1935, Mathematical Proceedings of the Cambridge Philosophical Society.

[16]  James O. Berger,et al.  Overall Objective Priors , 2015, 1504.02689.

[17]  J. Wishart,et al.  What Is "Probable Error"? , 2022 .

[18]  M. Bayarri Inferencia bayesiana sobre el coeficiente de correlacion de una poblacion normal bivariante , 1981 .

[19]  Dongchu Sun,et al.  Objective priors for the bivariate normal model , 2008, 0804.0987.

[20]  H. Iyer,et al.  Fiducial Generalized Confidence Intervals , 2006 .

[21]  T. MacRobert Higher Transcendental Functions , 1955, Nature.

[22]  W. J. DeCoursey,et al.  Introduction: Probability and Statistics , 2003 .

[23]  Eric-Jan Wagenmakers,et al.  A Tutorial on Fisher Information , 2017, 1705.01064.

[24]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[25]  Kerstin Vogler,et al.  Table Of Integrals Series And Products , 2016 .

[26]  Stephen M. Stigler,et al.  c ○ Institute of Mathematical Statistics, 2007 The Epic Story of Maximum Likelihood , 2022 .