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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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Power prior elicitation in Bayesian quantile regression [PDF]
, 2011 This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2011 Rahim Alhamzawi and Keming Yu.We address a quantile dependent prior for Bayesian quantile regression.
Rahim Alhamzawi +3 more
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Ensemble quantile classifier [PDF]
Computational Statistics & Data Analysis, 2020 Both the median-based classifier and the quantile-based classifier are useful for discriminating high-dimensional data with heavy-tailed or skewed inputs. But these methods are restricted as they assign equal weight to each variable in an unregularized way.
Yuanhao Lai, Ian McLeod
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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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Penalized flexible Bayesian quantile regression [PDF]
, 2012 Copyright © 2012 SciResThis article has been made available through the Brunel Open Access Publishing Fund.The selection of predictors plays a crucial role in building a multiple regression model. Indeed, the choice of a suitable subset of predictors can
Yu, K, Alkenani, A, Alhamzawi, R
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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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ggplot2 Compatible Quantile-Quantile Plots in R [PDF]
The R Journal, 2019 Q-Q plots allow us to assess univariate distributional assumptions by comparing a set of quantiles from the empirical and the theoretical distributions in the form of a scatterplot. To aid in the interpretation of Q-Q plots, reference lines and confidence bands are often added.
Alexandre Almeida +2 more
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