Results 31 to 40 of about 3,431,698 (356)
Vector quantile regression [PDF]
, 2014 We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y, taking values in ℝd given covariates Z=z, taking values in ℝk, is a map u↦QY∣Z(u,z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U
Guillaume Carlier +2 more
openaire +5 more sources
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
doaj +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
core +1 more source
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
Gradient boosting for extreme quantile regression [PDF]
Extremes, 2021 Extreme quantile regression provides estimates of conditional quantiles outside the range of the data. Classical quantile regression performs poorly in such cases since data in the tail region are too scarce.
J. Velthoen +3 more
semanticscholar +1 more source
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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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
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
core +2 more sources
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
doaj +1 more source