Results 11 to 20 of about 719 (114)
Bounding the maximum likelihood degree [PDF]
, 2015 Maximum likelihood estimation is a fundamental computational problem in statistics. In this note, we give a bound for the maximum likelihood degree of algebraic statistical models for discrete data.
Budur, Nero, Wang, Botong
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Improved estimation in a non-Gaussian parametric regression [PDF]
, 2011 The paper considers the problem of estimating the parameters in a continuous time regression model with a non-Gaussian noise of pulse type. The noise is specified by the Ornstein-Uhlenbeck process driven by the mixture of a Brownian motion and a compound
Pchelintsev, Evgeny
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Generating VaR scenarios with product beta distributions [PDF]
, 2018 We propose a Monte Carlo simulation method to generate stress tests by VaR scenarios under Solvency II for dependent risks on the basis of observed data.
Pfeifer, Dietmar, Ragulina, Olena
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On the eigenvalues of the spatial sign covariance matrix in more than two dimensions [PDF]
, 2016 Acknowledgments Alexander Dürre was supported in part by the Collaborative Research Grant 823 of the German Research Foundation. David E. Tyler was supported in part by the National Science Foundation grant DMS-1407751. A visit of Daniel Vogel to David E.
Dürre, Alexander +2 more
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On a class of norms generated by nonnegative integrable distributions
Dependence Modeling, 2019 We show that any distribution function on ℝd with nonnegative, nonzero and integrable marginal distributions can be characterized by a norm on ℝd+1, called F-norm. We characterize the set of F-norms and prove that pointwise convergence of a sequence of F-
Falk Michael, Stupfler Gilles
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Checkerboard copula defined by sums of random variables
Dependence Modeling, 2020 We consider the problem of finding checkerboard copulas for modeling multivariate distributions. A checkerboard copula is a distribution with a corresponding density defined almost everywhere by a step function on an m-uniform subdivision of the unit ...
Kuzmenko Viktor +2 more
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Law of Log Determinant of Sample Covariance Matrix and Optimal Estimation of Differential Entropy for High-Dimensional Gaussian Distributions [PDF]
, 2013 Differential entropy and log determinant of the covariance matrix of a multivariate Gaussian distribution have many applications in coding, communications, signal processing and statistical inference.
Cai, T. Tony +2 more
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Sampling in the Analysis Transform Domain [PDF]
, 2015 Many signal and image processing applications have benefited remarkably from the fact that the underlying signals reside in a low dimensional subspace. One of the main models for such a low dimensionality is the sparsity one.
Giryes, Raja
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Some remarks on a pair of seemingly unrelated regression models
Open Mathematics, 2019 Linear regression models are foundation of current statistical theory and have been a prominent object of study in statistical data analysis and inference.
Hou Jian, Zhao Yong
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New Algorithms for $M$-Estimation of Multivariate Scatter and Location [PDF]
, 2015 We present new algorithms for $M$-estimators of multivariate scatter and location and for symmetrized $M$-estimators of multivariate scatter. The new algorithms are considerably faster than currently used fixed-point and related algorithms. The main idea
Duembgen, Lutz +2 more
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