Results 21 to 30 of about 30,799 (217)
Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions
Econometrics, 2021 In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression.
Jau-er Chen +2 more
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Estimating extreme bivariate quantile regions [PDF]
Extremes, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Einmahl, J.H.J. +2 more
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Accurate Quantile Estimation for Skewed Data Streams Using Nonlinear Interpolation
IEEE Access, 2018 Quantile estimation is a fundamental method to generate the descriptions of the distribution of data for data management and analysis. Although the investigation and design of efficient quantile estimation algorithm has attracted much study, the problem ...
Jun Liu +3 more
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Unimodality of Parametric Linear Programming Solutions and Efficient Quantile Estimation
AppliedMath, 2023 For linear optimization problems with a parametric objective, so-called parametric linear programs (PLP), we show that the optimal decision values are, under few technical restrictions, unimodal functions of the parameter, at least in the two-degrees-of ...
Sara Mollaeivaneghi +2 more
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Control Variates for Quantile Estimation [PDF]
Management Science, 1987 New point and interval estimators for quantiles that employ a control variate are introduced. The properties of these estimators do not depend on the usual assumption of joint normality between the random variable of interest and the control. Illustrative examples for queueing and stochastic activity network models are given.
Jason C. Hsu, Barry L. Nelson
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Complexity, 2021 This study proposes a novel approach that incorporates rolling-window estimation and a quantile causality test. Using this approach, Google Trends and Bitcoin price data are used to empirically investigate the time-varying quantile causality between ...
Jianqin Hang, Xu Zhang
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Quantile-Wavelet Nonparametric Estimates for Time-Varying Coefficient Models
Mathematics, 2022 The paper considers quantile-wavelet estimation for time-varying coefficients by embedding a wavelet kernel into quantile regression. Our methodology is quite general in the sense that we do not require the unknown time-varying coefficients to be smooth ...
Xingcai Zhou, Guang Yang, Yu Xiang
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Generalized linear mixed quantile regression with panel data.
PLoS ONE, 2020 A new generalized linear mixed quantile model for panel data is proposed. This proposed approach applies GEE with smoothed estimating functions, which leads to asymptotically equivalent estimation of the regression coefficients.
Xiaoming Lu, Zhaozhi Fan
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Interval Estimation of Value-at-Risk Based on Nonparametric Models
Econometrics, 2018 Value-at-Risk (VaR) has become the most important benchmark for measuring risk in portfolios of different types of financial instruments. However, as reported by many authors, estimating VaR is subject to a high level of uncertainty.
Hussein Khraibani +2 more
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Scaling of High-Quantile Estimators [PDF]
Journal of Applied Probability, 2011 Enhanced by the global financial crisis, the discussion about an accurate estimation of regulatory (risk) capital a financial institution needs to hold in order to safeguard against unexpected losses has become highly relevant again. The presence of heavy tails in combination with small sample sizes turns estimation at such extreme quantile levels into
Degen, Matthias, Embrechts, Paul
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