Results 11 to 20 of about 162 (71)
A Central Limit Theorem for non-overlapping return times
, 2005 Define the non-overlapping return time of a random process to be the number of blocks that we wait before a particular block reappears. We prove a Central Limit Theorem based on these return times.
Johnson, Oliver
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Measuring the Tail Risk: An Asymptotic Approach [PDF]
, 2018 The risk exposure of a business line could be perceived in many ways and is sensitive to the exercise that is performed. One way is to understand the effect of some common/reference risk over the performance of the business line in question, but ...
Asimit, A.V., Li, J.
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Estimating sufficient reductions of the predictors in abundant high-dimensional regressions [PDF]
, 2012 We study the asymptotic behavior of a class of methods for sufficient dimension reduction in high-dimension regressions, as the sample size and number of predictors grow in various alignments.
Cook, R. Dennis +2 more
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Sparse permutation invariant covariance estimation
, 2007 The paper proposes a method for constructing a sparse estimator for the inverse covariance (concentration) matrix in high-dimensional settings. The estimator uses a penalized normal likelihood approach and forces sparsity by using a lasso-type penalty ...
Bickel, Peter J. +3 more
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On kernel-based estimation of conditional Kendall's tau: finite-distance bounds and asymptotic behavior [PDF]
, 2019 We study nonparametric estimators of conditional Kendall's tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic bounds with explicit constants, that hold with high probabilities.
Derumigny, Alexis, Fermanian, Jean-David
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Measuring and testing dependence by correlation of distances
, 2008 Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation ...
Bakirov, Nail K. +2 more
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Detection boundary in sparse regression [PDF]
, 2010 We study the problem of detection of a p-dimensional sparse vector of parameters in the linear regression model with Gaussian noise. We establish the detection boundary, i.e., the necessary and sufficient conditions for the possibility of successful ...
Ingster, Yuri I. +2 more
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Distance covariance in metric spaces
, 2013 We extend the theory of distance (Brownian) covariance from Euclidean spaces, where it was introduced by Sz\'{e}kely, Rizzo and Bakirov, to general metric spaces. We show that for testing independence, it is necessary and sufficient that the metric space
Lyons, Russell
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Extremes for coherent risk measures [PDF]
, 2016 Various concepts appeared in the existing literature to evaluate the risk exposure of a financial or insurance firm/subsidiary/line of business due to the occurrence of some extreme scenarios.
Asimit, A.V., Li, J.
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Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions
Dependence ModelingKendall’s tau and conditional Kendall’s tau matrices are multivariate (conditional) dependence measures between the components of a random vector. For large dimensions, available estimators are computationally expensive and can be improved by averaging ...
van der Spek Rutger, Derumigny Alexis
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