A continuous metric scaling solution for a random variable
Carles M. Cuadras,J. Fortiana +1 more
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In this paper, a countable set of uncorrelated random variables is obtained from an arbitary continuous random variable X, and the properties of these variables allow us to regard them as principal axes for X with respect to the distance function d ( u, v ) = [formula].About:
This article is published in Journal of Multivariate Analysis.The article was published on 1995-01-01 and is currently open access. It has received 65 citations till now. The article focuses on the topics: Random element & Multivariate random variable.read more
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The Dangers of Extreme Counterfactuals
Gary King,Langche Zeng +1 more
TL;DR: A proof that inferences farther from the data allow more model dependence is offered and easy-to-apply methods to evaluate how model dependent the authors' answers would be to specified counterfactuals are developed.
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When Can History Be Our Guide? The Pitfalls of Counterfactual Inference
Gary King,Langche Zeng +1 more
TL;DR: This paper develops easy-to-apply methods to evaluate counterfactuals that do not require sensitivity testing over specified classes of models and finds evidence that many scholars are inadvertently drawing conclusions based more on modeling hypotheses than on evidence in the data.
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On the Covariance between Functions
TL;DR: In this paper, the covariance between the functions of two random variables is obtained in terms of the cumulative distribution function, which generalizes previous formulae given by W. Hoeffding (1940, Schriften Math. Inst. Univ. Berlin5, 181?233) and K. V. Mardia (1967, Biometrika54, 235?249).
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A convex hull approach to counterfactual analysis of trade openness and growth
TL;DR: In this paper, the authors apply a convex hull approach to counterfactual analysis of trade openness and growth in Africa, and find that several countries do not fall within the convex-hull of the observed data.
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Some distance properties of latent root and vector methods used in multivariate analysis
TL;DR: In this paper, the authors derived necessary and sufficient conditions for a solution to exist in real Euclidean space for a multivariate multivariate sample of size n as points P1, P2,..., PI in a Euclidian space and discussed the interpretation of the distance A(Pi, Pj) between the ith and jth members of the sample.
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Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
TL;DR: In this article, a general method for calculating the limiting distributions of these criteria is developed by reducing them to corresponding problems in stochastic processes, which in turn lead to more or less classical eigenvalue and boundary value problems for special classes of differential equations.
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Empirical processes with applications to statistics
Galen R. Shorack,Jon A. Wellner +1 more
TL;DR: In this paper, a broad cross-section of the literature available on one-dimensional empirical processes is summarized, with emphasis on real random variable processes as well as a wide-ranging selection of applications in statistics.
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A Test of Goodness of Fit
TL;DR: The Kolmogorov test as discussed by the authors is a distribution-free test of goodness of fit that is sensitive to discrepancies at the tails of the distribution rather than near the median.