Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Best approximation of the identity mapping: The case of variable finite memory
Journal of Approximation Theory
Optimal multilinear estimation of a random vector under constraints of causality and limited memory
Computational Statistics & Data Analysis
Covariance estimation in full- and reduced-dimensionality image classification
Image and Vision Computing
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This paper derives and evaluates an algorithm for estimating normal covariances. A particular concern is the performance of the estimator when the dimension of the space exceeds the number of observations. The algorithm is simple, tolerably well founded, and seems to be more accurate for its purpose than the alternatives. Other topics discussed are the joint estimation of variances in one and many dimensions; the loss function appropriate to a variance estimator; and its connection with a certain Bayesian prescription.