Quotient spaces and statistical models

  • Mccullagh P
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Abstract

The purpose of this paper is to draw attention to the widespread occurrence of quotient spaces in statistical work. Quotient spaces are intrinsic to probability distributions, residuals and interaction in linear models, covariance functions and variograms of stochastic processes, etc. The theme is that explicit recognition of the quotient space can offer surprising conceptual simplification. The advantages of working directly with the quotient space are hard to describe in general. As the examples demonstrate, the answer lies partly in directness of approach.L'auteur fait ressortir l'ubiquité de la notion d'espace quotient en statistique. Il montre que cette structure est intrinsèque aux lois de probabilité, aux résidus et aux interactions dans les modèles linéaires, aux fonc‐tions de covariance et aux variogrammes des processus stochastiques, etc. Quoiqu'il soit difficile de décrire en toute généralité les avantages liés a l'emploi d'espaces quotients, l'auteur démontre par des exemples que la reconnaissance explicite de cette structure suggère sou vent une approche à la fois plus directe et plus simple au plan conceptuel.

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APA

Mccullagh, P. (1999). Quotient spaces and statistical models. Canadian Journal of Statistics, 27(3), 447–456. https://doi.org/10.2307/3316103

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