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Research Article Matrix-Variate Probabilistic Model for Canonical Correlation Analysis

by Mehran Safayani, Mohammad Taghi, Manzuri Shalmani
"... Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Motivated by the fact that in computer vision data samples are matrices, in this paper, we propose a matrix-variate probabilistic model for canonic ..."
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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

Fitting A Second-Order Parametric Distribution Conditioned on an Explanatory Variable Using Maximum Likelihood Estimation

by David E Burmaster , Kimberly M Thompson
"... 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, ..."
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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

MODELING EXTREME VALUES OF PROCESSES OBSERVED AT IRREGULAR TIME STEPS: APPLICATION TO

by unknown authors
"... This work is motivated by the analysis of the extremal behavior of buoy and satellite data describing wave conditions in the North Atlantic Ocean. The available data sets consist of time series of significant wave height (Hs) with irregular time sampling. In such a situation, the usual statistical m ..."
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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

port Vector Machines, Kernel Fisher Discriminant analysis

by Sebastian Mika, Koji Tsuda
"... Abstract | This review provides an introduction to Sup- ..."
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Abstract | This review provides an introduction to Sup-

© Institute of Mathematical Statistics, 2012 Statistical Modeling of Spatial Extremes1

by A. C. Davison, S. A. Padoan, M. Ribatet
"... Abstract. The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This ar-ticle reviews recent progress in the statistical modeling of spatial e ..."
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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

SIGNIFICANT WAVE HEIGHT

by unknown authors
"... ar ..."
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unknown title

by Helena Susana, Afonso Alves, Helena Susana, Afonso Alves , 2011
"... Corporate Governance determinants of voluntary disclosure and its effects on information asymmetry: an analysis for Iberian Peninsula listed companies. ..."
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Corporate Governance determinants of voluntary disclosure and its effects on information asymmetry: an analysis for Iberian Peninsula listed companies.

CORRECTING FOR PRECIPITATION EFFECTS IN SATELLITE-BASED PASSIVE MICROWAVE TROPICAL CYCLONE INTENSITY ESTIMATES

by Capt Wacker Robert S, Robert S. Wacker , 2005
"... 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 comments ..."
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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

AND MATHEMATICAL ENGINEERING

by Madeleine Udell, Professor Lester Mackey , 2015
"... ii ..."
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IEEE TRANSACTIONS ON INFORMATION THEORY (SUBMITTED) 1 Noisy Matrix Completion under Sparse Factor Models

by Akshay Soni, Swayambhoo Jain, Jarvis Haupt, Stefano Gonella
"... ar ..."
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