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Confidence Sets for Ratios: A Purely Geometric Approach To Fieller’s Theorem
We present a simple, geometric method to construct Fieller's exact confidence sets for ratios of jointly normally distributed random variables. Contrary to previous geometric approaches in the literature, our method is valid in the general case where both sample mean and covariance are unknown. Moreover, not only the construction but also its proof are purely geometric and elementary, thus giving intuition into the nature of the confidence sets.
@techreport{3172, title = {Confidence Sets for Ratios: A Purely Geometric Approach To Fieller's Theorem}, abstract = {We present a simple, geometric method to construct Fieller's exact confidence sets for ratios of jointly normally distributed random variables. Contrary to previous geometric approaches in the literature, our method is valid in the general case where both sample mean and covariance are unknown. Moreover, not only the construction but also its proof are purely geometric and elementary, thus giving intuition into the nature of the confidence sets.}, number = {133}, organization = {Max-Planck-Gesellschaft}, institution = {Max Planck Institute for Biological Cybernetics}, school = {Biologische Kybernetik}, year = {2004}, slug = {3172}, author = {von Luxburg, U. and Franz, VH.} }