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Jong-Min Kim, Chanho Cho, Chulhee Jun and Won Yong Kim
This paper examines the effect of board characteristics, especially board independence, on firm performance from a dynamic perspective through copula-based quantile regression approaches, which allow us to focus on changes at different points in the dist...
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Abdullah S. Al-Jawarneh, Ahmed R. M. Alsayed, Heba N. Ayyoub, Mohd Tahir Ismail, Siok Kun Sek, Kivanç Halil Ariç and Giancarlo Manzi
Recently, there has been an increased focus on enhancing the accuracy of machine learning techniques. However, there is the possibility to improve it by selecting the optimal tuning parameters, especially when data heterogeneity and multicollinearity exi...
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Lethiwe Nzama, Thanda Sithole and Sezer Bozkus Kahyaoglu
Purpose: This paper aims to investigate the impact of government effectiveness on trade and financial openness in 35 selected countries around the globe. Design/methodology/approach: A quantitative research approach was applied in the study using the gen...
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Siti Nadhirah Redzuan, Norazian Mohamed Noor, Nur Alis Addiena A. Rahim, Izzati Amani Mohd Jafri, Syaza Ezzati Baidrulhisham, Ahmad Zia Ul-Saufie, Andrei Victor Sandu, Petrica Vizureanu, Mohd Remy Rozainy Mohd Arif Zainol and György Deák
Malaysia has been facing transboundary haze events repeatedly, in which the air contains extremely high particulate matter, particularly PM10, which affects human health and the environment. Therefore, it is crucial to understand the characteristics of P...
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Melpomeni Nikou and Panagiotis Tziachris
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Sanlei Dang, Long Peng, Jingming Zhao, Jiajie Li and Zhengmin Kong
In this paper, a novel short-term load forecasting method amalgamated with quantile regression random forest is proposed. Comprised with point forecasting, it is capable of quantifying the uncertainty of power load. Firstly, a bespoke 2D data preprocessi...
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Innocent Mudhombo and Edmore Ranganai
Although the variable selection and regularization procedures have been extensively considered in the literature for the quantile regression (????)
(
Q
R
)
scenario via penalization, many such procedures fail to deal with data aberrations in the design ...
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Jennie Molinder, Sebastian Scher, Erik Nilsson, Heiner Körnich, Hans Bergström and Anna Sjöblom
A probabilistic machine learning method is applied to icing related production loss forecasts for wind energy in cold climates. The employed method, called quantile regression forests, is based on the random forest regression algorithm. Based on the perf...
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Liqiong Chen, Antonio F. Galvao and Suyong Song
This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic properties of...
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Congbo Chen and Azhong Ye
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Sorin Gabriel Anton, Mihaela Onofrei, Emilia Gogu, Bogdan Constantin Neculau and Florin Mihai
The paper aims to examine the relationship between leverage and firm growth and the impact of fiscal policy on this relationship using a panel data quantile regression approach. Employing a sample of gazelles from emerging Europe for the 2006?2014 period...
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Dat T. Nguyen, Tu D. Q. Le and Tin H. Ho
This study empirically presents evidence of nonlinearity and heterogeneity relation between intellectual capital and risk-taking for the Vietnamese banking system. We used quantile regression methods on a data set of 30 Vietnamese banks from 2007 to 2019...
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Chung-Chu Chuang, Chung-Min Tsai, Hsiao-Chen Chang and Yi-Hsien Wang
Electronics companies are facing global economic and trade competition. As patents can form an endowment shield that protects the development of corporate capabilities, companies are actively increasing their number of patents and attaching importance to...
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Tu D. Q. Le and Dat T. Nguyen
We empirically investigate the impact of capital structure on bank profitability using a quantile regression method in the Vietnamese banking system during 2007?2019. Our results suggest that the nonlinear relationship between capitalization and bank pro...
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Ngandu Balekelayi and Solomon Tesfamariam
Proactive management of wastewater pipes requires the development of deterioration models that support maintenance and inspection prioritization. The complexity and the lack of understanding of the deterioration process make this task difficult. A semipa...
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Lei Zhang, Lun Xie, Qinkai Han, Zhiliang Wang and Chen Huang
Based on quantile regression (QR) and kernel density estimation (KDE), a framework for probability density forecasting of short-term wind speed is proposed in this study. The empirical mode decomposition (EMD) technique is implemented to reduce the noise...
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Jau-er Chen and Chen-Wei Hsiang
We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heteroge...
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Ashkan Zarnani, Soheila Karimi and Petr Musilek
Information about forecast uncertainty is vital for optimal decision making in many domains that use weather forecasts. However, it is not available in the immediate output of deterministic numerical weather prediction systems. In this paper, we investig...
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Alex Golodnikov, Viktor Kuzmenko and Stan Uryasev
A popular risk measure, conditional value-at-risk (CVaR), is called expected shortfall (ES) in financial applications. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a function of ...
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Faustin Habyarimana, Temesgen Zewotir and Shaun Ramroop
Childhood anemia is among the most significant health problems faced by public health departments in developing countries. This study aims at assessing the determinants and possible spatial effects associated with childhood anemia in Rwanda. The 2014/201...
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