for canonical correlation analysis (CCA). Unlike probabilistic CCA which converts the image samples into the vectors, our method uses the original image matrices for data representation. We show that the maximum likelihood parameter estimation of the model leads to the two-dimensional canonical correlation

Abstract We show how to use the method of maximum likelihood estimation (MLE) to fit a second-order parametric distribution conditioned on a single explanatory variable to data. To illustrate the method, we demonstrate how a second-order LogNormal distribution, conditioned on the population served

methods for analyzing extreme values cannot be used directly. The method proposed in this paper is an extension of the peaks over threshold (POT) method, where the distribution of a process above a high threshold is approximated by a max-stable process whose parameters are estimated by maximizing a

Abstract | This review provides an introduction to Sup-

extremes, starting with sketches of the necessary elements of extreme value statistics and geostatistics. The main types of statistical models thus far proposed, based on latent variables, on copulas and on spatial max-stable processes, are described and then are compared by application to a data set

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Corporate Governance determinants of voluntary disclosure and its effects on information asymmetry: an analysis for Iberian Peninsula listed companies.

Public reporting burden for this collection of Information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send

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