Article
Mathematics, Applied
Qingsong Shan, Qianning Liu
Summary: This paper introduces a new method for measuring functional dependence called MFD, which uses a beta kernel estimator. The proposed estimator is shown to be highly accurate in estimation through simulated examples and analysis of real data.
Article
Economics
Michele Leonardo Bianchi, Giovanni De Luca, Giorgia Rivieccio
Summary: This paper demonstrates how to estimate CoVaR based on models that consider stylized facts about equity log returns, including heavy tails, negative skew, asymmetric dependence, and volatility clustering. Different models are compared using data from January 2007 to March 2020. The empirical study shows the importance of capturing time-varying dynamics of volatility in measuring CoVaR and highlights the need for an accurate assessment of tail heaviness and dependence structure in evaluating this systemic risk measure.
INTERNATIONAL JOURNAL OF FORECASTING
(2023)
Article
Engineering, Electrical & Electronic
Carlos D. Zuluaga-Rios, Cristian Guarnizo-Lemus
Summary: This paper proposes and validates three different approaches for estimating nodal voltages in DC-microgrids. The experimental results indicate that the Kalman filter approach outperforms the other methods in terms of performance.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Computer Science, Theory & Methods
Fabrizio Durante, Juan Fernandez-Sanchez, Manuel Ubeda-Flores
Summary: The probability mass distribution of a class of copulas that are invariant under univariate truncation is presented, and it is demonstrated how the (differential) properties of the copula's generator can identify the singular and absolutely continuous components of the induced measure and their support.
FUZZY SETS AND SYSTEMS
(2022)
Article
Mathematics
Mhamed Mesfioui, Mohamed Kayid
Summary: This paper applies the residual probability function to analyze the survival probability of two used components relative to each other, discussing the behavior in terms of underlying dependence and considering the residual probability order in the dependent case. The study in the class of Archimedean survival copulas shows that the residual probability order implies the usual stochastic order in the reversed direction and the hazard rate order concludes the residual probability order.
Article
Mathematics
Lu Lu, Sujit Ghosh
Summary: In the fields of finance, insurance, and system reliability, measuring the dependence among variables is crucial. This article proposes a new empirical checkerboard copula model that provides a smooth estimator and offers more accurate estimation of multiple dependence measures.
Article
Mathematics, Applied
Fatimah Alshahrani, Wahiba Bouabsa, Ibrahim M. Almanjahie, Mohammed Kadi Attouch
Summary: Traditionally, regression problems are examined using univariate characteristics, but this study aims to examine a nonparametric estimator of a scalar response variable's function of a density and mode, given a functional variable when the data are spatially dependent. The estimator is derived and established by combining the local linear and the k nearest neighbors methods, and its uniform consistency in the number of neighbors (UNN) is proved. The new estimator is then applied to simulated and real data to demonstrate its efficacy and superiority compared to existing competing estimators.
Article
Statistics & Probability
Florian Griessenberger, Robert R. Junker, Wolfgang Trutschnig
Summary: This article introduces a copula-based multivariate dependence measure for quantifying the extent of dependence between random variables. A checker-board estimator is derived and shown to have strong consistency. Simulation results validate the performance of the estimator.
ELECTRONIC JOURNAL OF STATISTICS
(2022)
Article
Statistics & Probability
Nikolaos Ignatiadis, Sujayam Saha, Dennis L. Sun, Omkar Muralidharan
Summary: In this study, we propose a method called Aurora for the estimation of effect sizes using multiple observations per unit. Aurora achieves near-Bayes optimal mean squared error without any assumptions or knowledge about the effect size distribution or noise. It leverages replication and recasts the estimation problem as a general regression problem. Aurora with linear regression matches the performance of various estimators including sample mean, trimmed mean, sample median, and James-Stein shrunk versions thereof.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Article
Automation & Control Systems
Lasse Petersen, Niels Richard Hansen
Summary: This paper develops a nonparametric test for conditional independence by combining the partial copula with a quantile regression based method for estimating the nonparametric residuals. The resulting test is demonstrated to be sound under complicated data generating distributions and competitive to other state-of-the-art conditional independence tests, with superior power in cases with conditional variance heterogeneity of X and Y given Z.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Engineering, Environmental
Youzhi Wang, Ping Guo
Summary: A copula-measure based interval multi-objective multi-stage stochastic chance-constrained programming (CMIMOMSP) model is proposed for water consumption optimization. It introduces multi-objective programming to improve the traditional stochastic chance-constrained programming by considering relationships among various factors. The model is applied to a case study in the Heihe River Basin, showing different impacts of optimistic-pessimistic factors on water allocation for different sectors.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2021)
Article
Engineering, Industrial
Kunsong Lin, Yunxia Chen
Summary: This paper conducts a two-dimensional warranty analysis on data with heterogeneity in terms of both age and usage. Two models are developed to evaluate the severity of warranty claims, with different dependence structures. It is found that over 85% of claims are classified as normal failures, and local dependence structures may vary.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Statistics & Probability
Xi Chen, Weidong Liu, Yichen Zhang
Summary: This article investigates distributed estimation and inference for a general statistical problem by proposing a new multi-round distributed estimation procedure to overcome restrictions on the number of machines. The method introduces a computationally efficient estimator for Sigma(-1)w, applicable to nondifferentiable losses, facilitating inference for the empirical risk minimizer.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2022)
Article
Statistics & Probability
Mona Azadkia, Sourav Chatterjee
Summary: This study introduces a coefficient for measuring the conditional dependence between random variables without distributional assumptions, and develops a new variable selection algorithm based on this coefficient. The method is model-free, parameter-free, and provably consistent under sparsity assumptions, with applications to both synthetic and real data sets.
ANNALS OF STATISTICS
(2021)
Article
Statistics & Probability
Pascal Bianchi, Kevin Elgui, Francois Portier
Summary: The paper proposes a test statistic that is an explicit Cramer-von Mises transformation of a weighted partial copula function. The regions of rejection are computed using a bootstrap procedure that generates samples from the product measure of the estimated conditional marginals. The paper establishes convergence rates for the weighted partial copula process and the test statistic, as well as weak convergence under the null hypothesis of the normalized test statistic, under certain conditions on the estimated margins.
JOURNAL OF MULTIVARIATE ANALYSIS
(2023)
