Results 21 to 30 of about 56,994 (264)
Mixtures of quantile regressions [PDF]
Computational Statistics & Data Analysis, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Qiang, Yao, Weixin
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Quantile regression in high-dimension with breaking [PDF]
Journal of Statistical Theory and Applications (JSTA), 2013 The paper considers a linear regression model in high-dimension for which the predictive variables can change the influence on the response variable at unknown times (called change-points).
Gabriela Ciuperca
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Comparative Economic Research, 2012 In a number of applications, a crucial problem consists in describing and analyzing the influence of a vector Xi of covariates on some real-valued response variable Yi.
Grażyna Trzpiot
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Nonparametric C- and D-vine-based quantile regression
Dependence Modeling, 2022 Quantile regression is a field with steadily growing importance in statistical modeling. It is a complementary method to linear regression, since computing a range of conditional quantile functions provides more accurate modeling of the stochastic ...
Tepegjozova Marija +3 more
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Nonparametric Smoothing for Extremal Quantile Regression with Heavy Tailed Data
Revstat Statistical Journal, 2021 In several different fields, it is interested in analyzing the upper or lower tail quantile of the underlying distribution rather than mean or center quantile.
Takuma Yoshida
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Pyramid Quantile Regression [PDF]
Journal of Computational and Graphical Statistics, 2019 Quantile regression models provide a wide picture of the conditional distributions of the response variable by capturing the effect of the covariates at different quantile levels. In most applications, the parametric form of those conditional distributions is unknown and varies across the covariate space, so fitting the given quantile levels ...
T. Rodrigues +2 more
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Journal of Water and Climate Change, 2023 This research utilized Bayesian and quantile regression techniques to analyze trends in discharge levels across various seasons for three stations in the Gorganroud basin of northern Iran. The study spanned a period of 50 years (1966–2016).
Khalil Ghorbani +3 more
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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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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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Local quantile regression [PDF]
Journal of Statistical Planning and Inference, 2013 Quantile regression is a technique to estimate conditional quantile curves. It provides a comprehensive picture of a response contingent on explanatory variables. In a flexible modeling framework, a specific form of the conditional quantile curve is not a priori fixed.
Wolfgang Karl Härdle +2 more
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