Results 21 to 30 of about 3,032,172 (354)

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, J.-L. Dortet-Bernadet, Y. Fan   +2 more
openaire   +4 more sources

Forecasting Value-at-Risk Using Deep Neural Network Quantile Regression

Journal of Financial Econometrics, 2023
In this article, we use a deep quantile estimator, based on neural networks and their universal approximation property to examine a non-linear association between the conditional quantiles of a dependent variable and predictors.
Ilias Chronopoulos, Aristeidis Raftapostolos, G. Kapetanios   +2 more
semanticscholar   +1 more source

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

Batch effects removal for microbiome data via conditional quantile regression

Nature Communications, 2022
Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Strategies designed for genomic data to mitigate batch effects usually fail to address the zero-inflated and over-
Wodan Ling, Jiuyao Lu, Ni Zhao, Anju Lulla, A. Plantinga, Weijia Fu, Angela Zhang, Hongjiao Liu, Hoseung Song, Zhigang Li, Jun Chen, T. Randolph, W. L. Koay, J. White, L. Launer, A. Fodor, K. Meyer, Michael C. Wu   +17 more
semanticscholar   +1 more source

The dynamic effect of information and communication technology and renewable energy on CO2 emission: Fresh evidence from panel quantile regression

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, M. Shabbir, Mohammad Haseeb, M. Kamal, Ahsan Anwar, Mohammad Faisal Khan, S. Malik   +6 more
semanticscholar   +1 more source

Smoothing Quantile Regressions [PDF]

Journal of Business & Economic Statistics, 2019
We propose to smooth the entire objective function, rather than only the check function, in a linear quantile regression context. Not only does the resulting smoothed quantile regression estimator yield a lower mean squared error and a more accurate Bahadur-Kiefer representation than the standard estimator, but it is also asymptotically differentiable.
Marcelo Fernandes, Emmanuel Guerre, Eduardo Horta   +2 more
openaire   +3 more sources

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 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
doaj   +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, C. Dombry, J. Cai, Sebastian Engelke   +3 more
semanticscholar   +1 more source

Comparison of Bayesian and frequentist quantile regressions in studying the trend of discharge changes in several hydrometric stations of the Gorganroud basin in Iran

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, Meysam Salarijazi, Sedigheh Bararkhanpour, Laleh Rezaei Ghaleh   +3 more
doaj   +1 more source