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Influence diagnostics in Gaussian spatial-temporal linear models with separable covariance
(2023)
In recent decades, there has been a growing interest in modeling spatial-temporal data, which can be found in many fields including geoscience, meteorology and ecology, among many others. The spatial-temporal dependence ...
Using Spatial Covariance Function for Antitrust Market DelineationUsing Spatial Covariance Function for Antitrust Market Delineation
(Sociedade Brasileira de Econometria, 2009)
Using spatial covariance function for antitrust market delineation
(Sociedade Brasileira de Econometria, 2009-05-01)
In this paper, an estimation of a Spatial Covariance Function was proposed for determining the relevant geographic market for a merger. This methodology was applied to a proposed merger between two competing Brazilian ...
C∗-algebraic covariant structures
(University of Houston, 2016)
© 2016 University of Houston. We introduce covariant structures {(script A, κ), (a, α), (ã, α)} formed of a separable C∗-algebra script A, a measurable twisted action (a, α) of the second-countable locally compact group G ...
C-*-Algebraic covariant structures
(Univ Houston, 2016)
We introduce covariant structures {(A, kappa), (a, alpha), ((a) over tilde, (alpha) over tilde)} formed of a separable C*-algebra A, a measurable twisted action (a, alpha) of the second-countable locally compact group G, ...
Robust estimators under a functional common principal components model
(Elsevier Science, 2017-09)
When dealing with several populations of functional data, equality of the covariance operators is often assumed even when seeking for a lower-dimensional approximation to the data. Usually, if this assumption does not hold, ...