Results 11 to 20 of about 315,996 (341)
Quantile Double Autoregression [PDF]
SSRN Electronic Journal, 2019 Many financial time series have varying structures at different quantile levels, and also exhibit the phenomenon of conditional heteroskedasticity at the same time. However, there is presently no time series model that accommodates both of these features.
Zhu, Qianqian, Li, Guodong
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Investigating the impacts of technological innovation and renewable energy on environmental pollution in countries selected by the International Renewable Energy Agency: A quantile regression approach [PDF]
Caspian Journal of Environmental Sciences, 2020 Investigating the factors affecting CO2 emissions has always been a challenge. One problem with existing studies is that these studies have been relied on mean-based regression approaches, such as ordinary least squares (OLS) or instrumental variables ...
Nasim Masoudi +2 more
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Smooth Quantile Normalization [PDF]
Biostatistics, 2016 AbstractBetween-sample normalization is a critical step in genomic data analysis to remove systematic bias and unwanted technical variation in high-throughput data. Global normalization methods are based on the assumption that observed variability in global properties is due to technical reasons and are unrelated to the biology of interest. For example,
Hicks, Stephanie C +5 more
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Journal of Business & Economic Statistics, 2021 This paper proposes a simple approach to estimate quantiles of daily financial returns directly from high-frequency data. We denote the resulting estimator as realized quantile (RQ) and use it to forecast tail risk measures, such as Value at Risk (VaR) and Expected Shortfall (ES).
Dimitriadis, Timo, Halbleib, Roxana
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Estimation of confidence intervals for quantiles in a finite population
Mathematical Modelling and Analysis, 2008 Confidence intervals provide a way of reporting an estimate of a population quantile along with some information about the precision of estimates. Some procedures that may be used to obtain estimates of confidence intervals for quantiles in a finite ...
Viktoras Chadyšas
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Online Monitoring of Wind Turbine Operation Efficiency and Optimization Based on Benchmark Values
IEEE Access, 2019 Improving the operational efficiency of wind turbines is an important way to enhance the competitiveness of wind power generation among new energy sources.
Yujiong Gu, Yue Xing
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Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review
Risks, 2018 One of the key components of financial risk management is risk measurement. This typically requires modeling, estimating and forecasting tail-related quantities of the asset returns’ conditional distribution.
Marco Bee, Luca Trapin
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Physio-Géo, 2016 The extreme rainfalls are the weather hazards that cause much damage and many casualties. The estimation of extreme rainfall is therefore of great interest to anticipate disasters such as floods and allow thoughtful planning of the territory.
Gneneyougo Émile Soro +4 more
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A Quantile-Based Approach for Transmission Expansion Planning
IEEE Access, 2020 Transmission expansion planning is an integral part of power system planning and consists of generating and selecting transmission proposals for maintaining sufficient transmission capacity to satisfy the electric load.
Jairo Cervantes, F. Fred Choobineh
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Choosing the Right Spatial Weighting Matrix in a Quantile Regression Model [PDF]
, 2013 This paper proposes computationally tractable methods for selecting the appropriate spatial weighting matrix in the context of a spatial quantile regression model.
Kostov, Phillip
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