Results 31 to 40 of about 3,477,506 (374)
High‐dimensional quantile regression: Convolution smoothing and concave regularization [PDF]
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2021 ℓ1 ‐penalized quantile regression (QR) is widely used for analysing high‐dimensional data with heterogeneity. It is now recognized that the ℓ1 ‐penalty introduces non‐negligible estimation bias, while a proper use of concave regularization may lead to ...
Kean Ming Tan, Lan Wang, Wen-Xin Zhou
semanticscholar +1 more source
M-quantile regression analysis of temporal gene expression data [PDF]
, 2009 In this paper, we explore the use of M-regression and M-quantile coefficients to detect statistical differences between temporal curves that belong to different experimental conditions.
Vinciotti, V, Yu, K
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Parametric Elliptical Regression Quantiles
Revstat Statistical Journal, 2020 The article extends linear and nonlinear quantile regression to the case of vector responses by generalizing multivariate elliptical quantiles to a regression context.
Daniel Hlubinka , Miroslav Šiman
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Frontiers in Environmental Science, 2022 Graphical Abstract Over the last few years, the rapid growth of information and communication technologies (ICT) has contributed to every sector of the economy; however, the environmental consequences of ICT should not be overlooked.
Yuzhao Wen +6 more
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Out-of-sample equity premium prediction: A complete subset quantile regression approach [PDF]
, 2013 This paper extends the complete subset linear regression framework to a quantile regression setting. We employ complete subset combinations of quantile forecasts in order to construct robust and accurate equity premium predictions.
Meligkotsidou, Loukia +3 more
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Fintech, financial inclusion and income inequality: a quantile regression approach
European Journal of Finance, 2020 Although theory suggests that financial market imperfections – mainly information asymmetries, market segmentation and transaction costs – prevent poor people from escaping poverty by limiting their access to formal financial services, new financial ...
Ayşegül Demir +3 more
semanticscholar +1 more source
The Journal of Economic Asymmetries, 2022 The COVID-19 pandemic has affected all sectors of the economy resulting in unprecedented challenges for market participants, policymakers, and practitioners.
A. Bossman, Zaghum Umar, T. Teplova
semanticscholar +1 more source
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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Factors Affecting Productivity of Upland and Lowland Rice Farms in Matalom, Leyte: A Quantile Regression Approach [PDF]
Review of Socio-Economic Research and Development Studies, 2017 This study investigates the determinants of productivity in selected upland and lowland rice farms in Matalom, Leyte using quantile regression approach. Data on rice production are obtained from 40 upland and 40 lowland rice farming households which are ...
Brenda M. Ramoneda, Junnel K. Pene
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Quantile regression, asset pricing and investment decision
IIMB Management Review, 2021 The present study compares the Fama-French three factor coefficient estimates obtained from both ordinary least squares (OLS) and quantile regression for 25 size-value sorted portfolios of BSE 500.
Moinak Maiti
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