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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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Batch effects removal for microbiome data via conditional quantile regression
Nature Communications, 2022 Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Strategies designed for genomic data to mitigate batch effects usually fail to address the zero-inflated and over-
Wodan Ling +17 more
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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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Annals of Statistics, 2021 Unlike the real line, the real space Rd, for d ≥ 2, is not canonically ordered. As a consequence, such fundamental univariate concepts as quantile and distribution functions, and their empirical counterparts, involving ranks and signs, do not canonically
M. Hallin +3 more
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Frontiers in Environmental Science, 2021 Sustainable development and reducing environmental pressure are major issues that concern developed as well as developing countries. Although researchers widely use carbon dioxide emissions and ecological footprint within the scope of environmental ...
Zeeshan Fareed +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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