Skovgaard, Lene Theil A Riemannian geometry of the multivariate normal model. (English) Zbl 0579.62033 Scand. J. Stat., Theory Appl. 11, 211-223 (1984). This paper deals with the geometry of multivariate normal distributions. First a representation of the model as a differentiable manifold is given. Then using the Fisher information as a Riemannian metric, the Riemannian geometry of the model has been studied. The theory has been illustrated by some examples from statistical inference. Reviewer: A.K.Gupta Cited in 1 ReviewCited in 55 Documents MathOverflow Questions: Complete statistical manifolds MSC: 62H05 Characterization and structure theory for multivariate probability distributions; copulas 62H10 Multivariate distribution of statistics 53B20 Local Riemannian geometry Keywords:affine connection; minimum distance estimators; test statistics; curvature tensor; geodesic distance estimators; geometry of multivariate normal distributions; Fisher information PDFBibTeX XMLCite \textit{L. T. Skovgaard}, Scand. J. Stat. 11, 211--223 (1984; Zbl 0579.62033)