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The Cauchy distribution is usually presented as a mathematical curiosity, an exception to the Law of Large Numbers, or even as an “Evil” distribution in some introductory courses. It therefore surprised us when Drton and Xiao Bernoulli 22 (2016) 38–59 proved the following result for m=2 and conjectured it for m3. Let X= (X₁, , X₌) and Y= (Y₁, , Y₌) be i. i. d. N (0, ), where =\₈₉\0 is an m m and arbitrary covariance matrix with ₉₉>0 for all 1 j m. Then =₉=₁^mw₉X₉{Y₉} (0, 1), \ as long as w= (w₁, , w₌) is independent of (X, Y), w₉0, j=1, , m, and ₉=₁^mw₉=1. In this note, we present an elementary proof of this conjecture for any m2 by linking Z to a geometric characterization of Cauchy (0, 1) given in Willams Ann. Math. Stat. 40 (1969) 1083–1085. This general result is essential to the large sample behavior of Wald tests in many applications such as factor models and contingency tables. It also leads to other unexpected results such as \₈=₁^m₉=₁^mw₈ₖ_₉₈₉X₈X₉ Lévy (0, 1). \ This generalizes the “super Cauchy phenomenon” that the average of m i. i. d. standard Lévy variables (i. e. , inverse chi-squared variables with one degree of freedom) has the same distribution as that of a single standard Lévy variable multiplied by m (which is obtained by taking w₉=1/m and to be the identity matrix).
Pillai et al. (Mon,) studied this question.