Results 51 to 60 of about 3,032,172 (354)

Penalized single-index quantile regression [PDF]

, 2013
This article is made available through the Brunel Open Access Publishing Fund. Copyright for this article is retained by the author(s), with first publication rights granted to the journal.
Yu, K
core   +1 more source

The roles of economic growth and health expenditure on CO2 emissions in selected Asian countries: a quantile regression model approach

Environmental science and pollution research international, 2021
Continuous economic growth and the rise in energy consumption are linked with environmental pollution. Demand for health care expenditure increased after the COVID-19 pandemic.
F. Bilgili, S. Kuşkaya, Masreka Khan, A. Awan, O. Türker   +4 more
semanticscholar   +1 more source

Local linear spatial quantile regression [PDF]

, 2009
Copyright @ 2009 International Statistical Institute / Bernoulli Society for Mathematical Statistics and Probability.Let {(Yi,Xi), i ∈ ZN} be a stationary real-valued (d + 1)-dimensional spatial processes.
Hallin, M, Lu, Z, Yu, K
core   +2 more sources

Prediction method of coal calorific value based on quantile regression

Gong-kuang zidonghua, 2022
At present, the traditional linear regression model is mainly used to predict the calorific value of coal. But it is difficult to express the complex relationship between independent variables and dependent variables.
ZHAO Xianzhi, CHEN Junlin
doaj   +1 more source

Quantile Regression

, 2014
A guide to the implementation and interpretation of Quantile Regression models. This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensive description of the main issues ...
Davino, Cristina, Furno, Marilena, Vistoccco, Domenico   +2 more
  +9 more sources

An Improved Interior Point Algorithm for Quantile Regression

IEEE Access, 2020
Quantile regression is a powerful statistical technique for estimating the quantiles of a conditional distribution on the values of covariates. It has been widely used in many fields.
Pan Zhao, Shenghua Yu
doaj   +1 more source

Fast calibrated additive quantile regression

, 2020
We propose a novel framework for fitting additive quantile regression models, which provides well calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diverse as those ...
Azzalini A., Brent R. P., Hastie T., Hothorn T., Jones M., Margaux Zaffran, Matteo Fasiolo, Raphaël Nedellec, Robert C., Simon N. Wood, Yannig Goude, Yee T. W.   +11 more
core   +1 more source

Bayesian quantile semiparametric mixed-effects double regression models

Statistical Theory and Related Fields, 2021
Semiparametric mixed-effects double regression models have been used for analysis of longitudinal data in a variety of applications, as they allow researchers to jointly model the mean and variance of the mixed-effects as a function of predictors ...
Duo Zhang, Liucang Wu, Keying Ye, Min Wang   +3 more
doaj   +1 more source

Functional coefficient quantile regression model with time-varying loadings

Journal of Applied Economics, 2023
This paper proposes a functional coefficient quantile regression model with heterogeneous and time-varying regression coefficients and factor loadings. Estimation of the model coefficients is done in two stages.
Alev Atak, Gabriel Montes-Rojas, Jose Olmo   +2 more
doaj   +1 more source

ReModels: Quantile Regression Averaging models

SoftwareX
Electricity price forecasts are essential for making informed business decisions within the electricity markets. Probabilistic forecasts, which provide a range of possible future prices rather than a single estimate, are particularly valuable for ...
Grzegorz Zakrzewski, Kacper Skonieczka, Mikołaj Małkiński, Jacek Mańdziuk   +3 more
doaj   +1 more source