Results 21 to 30 of about 2,329,699 (248)

Simulation Study of Autocorrelated Error Using Bayesian Quantile Regression

Science and Technology Indonesia, 2020
  The purpose of this study is to compare the ability of the Classical Quantile Regression method and the Bayesian Quantile Regression method in estimating models that contain autocorrelated error problems using simulation studies.
Nayla Desviona, Ferra Yanuar
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Fuzzy Semi-Parametric Logistic Quantile Regression Model

Wasit Journal for Pure Sciences, 2023
In this paper, the fuzzy semi-parametric logistic quantile regression model was studied in the absence of special conditions in the classical regression models.
Ahmed Razzaq, Ayad H. shemaila
doaj   +1 more source

Modeling Length of Hospital Stay for Patients With COVID-19 in West Sumatra Using Quantile Regression Approach

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021
This study aims to construct the model for the length of hospital stay for patients with COVID-19 using quantile regression and Bayesian quantile approaches.
Ferra Yanuar, Athifa Salsabila Deva, Maiyastri Maiyastri, Hazmira Yozza, Aidinil Zetra   +4 more
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Bayesian quantile regression [PDF]

, 2006
Recent work by Schennach(2005) has opened the way to a Bayesian treatment of quantile regression. Her method, called Bayesian exponentially tilted empirical likelihood (BETEL), provides a likelihood for data y subject only to a set of m moment conditions of the form Eg(y, θ) = 0 where θ is a k dimensional parameter of interest and k ...
Tony Lancaster, Sung Jae Jun
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Mixtures of quantile regressions [PDF]

Computational Statistics & Data Analysis, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Qiang, Yao, Weixin
openaire   +5 more sources

Spatial Quantile Regression

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
doaj   +1 more source

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
doaj   +1 more source

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, Zhou Jing, Claeskens Gerda, Czado Claudia   +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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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