Results 11 to 20 of about 691 (95)
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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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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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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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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Asymptotics of the two-stage spatial sign correlation [PDF]
, 2015 Acknowledgments This research was supported in part by the Collaborative Research Grant 823 of the German Research Foundation. The authors wish to thank the editors and referees for their careful handling of the manuscript.
Dürre, Alexander, Vogel, Daniel
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Dependence Modeling, 2013 We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas ...
Di Bernardino Elena, Rullière Didier
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Inference for copula modeling of discrete data: a cautionary tale and some facts
Dependence Modeling, 2017 In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula ...
Faugeras Olivier P.
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Dependence measure for length-biased survival data using copulas
Dependence Modeling, 2019 The linear correlation coefficient of Bravais-Pearson is considered a powerful indicator when the dependency relationship is linear and the error variate is normally distributed.
Bentoumi Rachid +2 more
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Moderate deviations of minimum contrast estimators under contamination [PDF]
, 2003 Since statistical models are simplifications of reality, it is important in estimation theory to study the behavior of estimators also under distributions (slightly) different from the proposed model.
Inglot, Tadeusz +1 more
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Volatility filtering in estimation of kurtosis (and variance)
Dependence Modeling, 2019 The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
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