Results 21 to 30 of about 30,567 (245)
How Do Financial Development and Renewable Energy Affect Consumption-Based Carbon Emissions?
Mathematical and Computational Applications, 2022 This paper bridges the gap in the literature by employing the novel quantile-on-quantile (QQ) approach, the quantile regression approach, and the nonparametric Granger causality test in quantiles to assess the effect of international trade on consumption-
Abraham Ayobamiji Awosusi +3 more
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Mathematics, 2023 The presence of nonignorable missing response variables often leads to complex conditional distribution patterns that cannot be effectively captured through mean regression.
Jingxuan Guo +7 more
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Mathematics, 2023 Space-time varying coefficient models, which are used to identify the effects of covariates that change over time and spatial location, have been widely studied in recent years. One such model, called the quantile regression model, is particularly useful
Bertho Tantular +3 more
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Nonparametric depth and quantile regression for functional data [PDF]
Bernoulli, 2019 We investigate nonparametric regression methods based on spatial depth and quantiles when the response and the covariate are both functions. As in classical quantile regression for finite dimensional data, regression techniques developed here provide insight into the influence of the functional covariate on different parts, like the center as well as ...
Chowdhury, Joydeep, Chaudhuri, Probal
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Quantile-dependent expressivity of serum C-reactive protein concentrations in family sets [PDF]
PeerJ, 2021 Background “Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., C-reactive protein, CRP) is high or low relative to its distribution. We have previously shown that the heritabilities
Paul T. Williams
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Fuzzy Semi-Parametric Logistic Quantile Regression Model
Wasit Journal for Pure Sciences, 2023 In this paper, the fuzzy semi-parametric logistic quantile regression model was studied in the absence of special conditions in the classical regression models.
Ahmed Razzaq, Ayad H. shemaila
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Journal of Marine Science and Engineering, 2022 Transportation is one of the major carbon sources in China. Container throughput is one of the main influencing factors of ports’ carbon emission budget, and accurate prediction of container throughput is of great significance to the study of carbon ...
Yuye Zou, Bohan Su, Yanhui Chen
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Quantile-dependent expressivity of plasma adiponectin concentrations may explain its sex-specific heritability, gene-environment interactions, and genotype-specific response to postprandial lipemia [PDF]
PeerJ, 2020 Background “Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. adiponectin) is high or low relative to its distribution.
Paul T. Williams
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Additive quantile mixed effects modelling with application to longitudinal CD4 count data
Scientific Reports, 2021 Quantile regression offers an invaluable tool to discern effects that would be missed by other conventional regression models, which are solely based on modeling conditional mean.
Ashenafi A. Yirga +3 more
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Heliyon, 2023 In a nonparametric quantile-on-quantile regression model, we analyze the asymmetric financial impact of the Russian-Ukrainian conflict-induced geopolitical risk (GPR) on the top-seven emerging (E7) and developed (G7) stock markets.
Ahmed Bossman, Mariya Gubareva
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