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Lixiong Yang, Hujie Bai & Mingjian Ren. (2023) Threshold quantile regression neural network. Applied Economics Letters 0:0, pages 1-11.
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Sanket Jantre. (2023) Bayesian quantile regression for longitudinal count data. Journal of Statistical Computation and Simulation 93:1, pages 103-127.
Read now
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Yoonsuh Jung, Steven N. MacEachern & Hang Joon Kim. (2021) Modified check loss for efficient estimation via model selection in quantile regression. Journal of Applied Statistics 48:5, pages 866-886.
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Felix Scheller & Benjamin R. Auer. (2018) How does the choice of Value-at-Risk estimator influence asset allocation decisions?. Quantitative Finance 18:12, pages 2005-2022.
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M.R. Muggeo, Mariangela Sciandra & Luigi Augugliaro. (2012) Quantile regression via iterative least squares computations. Journal of Statistical Computation and Simulation 82:11, pages 1557-1569.
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Anouar El Ghouch & Marc G. Genton. (2009) Local Polynomial Quantile Regression With Parametric Features. Journal of the American Statistical Association 104:488, pages 1416-1429.
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Articles from other publishers (38)
E. Di Lorenzo, G. Piscopo & M. Sibillo. (2023) Addressing the economic and demographic complexity via a neural network approach: risk measures for reverse mortgages. Computational Management Science 21:1.
Crossref
Crossref
Kokulo K. Lawuobahsumo, Bernardina Algieri & Arturo Leccadito. (2023) Forecasting cryptocurrencies returns: Do macroeconomic and financial variables improve tail expectation predictions?. Quality & Quantity.
Crossref
Crossref
Zhen-Yu Chen, Zhi-Ping Fan & Minghe Sun. (2023) Inventory Management With Multisource Heterogeneous Information: Roles of Representation Learning and Information Fusion. IEEE Transactions on Systems, Man, and Cybernetics: Systems 53:9, pages 5343-5355.
Crossref
Crossref
Ujjwal Singh, Petr Maca, Martin Hanel, Yannis Markonis, Rama Rao Nidamanuri, Sadaf Nasreen, Johanna Ruth Blöcher, Filip Strnad, Jiri Vorel, Lubomir Riha & Akhilesh Singh Raghubanshi. (2023) Hybrid multi-model ensemble learning for reconstructing gridded runoff of Europe for 500 years. Information Fusion 97, pages 101807.
Crossref
Crossref
Ruiting Hao, Qiwei Han, Lu Li & Xiaorong Yang. (2023) DAmcqrnn: An approach to censored monotone composite quantile regression neural network estimation. Information Sciences 638, pages 118986.
Crossref
Crossref
Zhen-Yu Chen. (2022) The value of probabilistic forecasting in emergency medical resource planning under uncertainty. Kybernetes 52:6, pages 1962-1975.
Crossref
Crossref
Frederik Boe Huttel, Inon Peled, Filipe Rodrigues & Francisco C. Pereira. (2022) Modeling Censored Mobility Demand Through Censored Quantile Regression Neural Networks. IEEE Transactions on Intelligent Transportation Systems 23:11, pages 21753-21765.
Crossref
Crossref
Yanlai Zhou, Di Zhu, Hua Chen, Shenglian Guo, Chong-Yu Xu & Fi-John Chang. (2022) Deep learning–based neural networks for day-ahead power load probability density forecasting. Environmental Science and Pollution Research 30:7, pages 17741-17764.
Crossref
Crossref
Ruiting Hao, Huanfeng Zheng & Xiaorong Yang. (2022) Data augmentation based estimation for the censored composite quantile regression neural network model. Applied Soft Computing 127, pages 109381.
Crossref
Crossref
Xingcai Zhou, Jiangyan Wang, Hongxia Wang & Jinguan Lin. (2022) Panel semiparametric quantile regression neural network for electricity consumption forecasting. Ecological Informatics 67, pages 101489.
Crossref
Crossref
Yanlai Zhou, Zhen Cui, Kangling Lin, Sheng Sheng, Hua Chen, Shenglian Guo & Chong-Yu Xu. (2022) Short-term flood probability density forecasting using a conceptual hydrological model with machine learning techniques. Journal of Hydrology 604, pages 127255.
Crossref
Crossref
Yichen Jia & Jong-Hyeon Jeong. (2022) Deep learning for quantile regression under right censoring: DeepQuantreg. Computational Statistics & Data Analysis 165, pages 107323.
Crossref
Crossref
Wanying Zhang, Yaoyao He & Shanlin Yang. (2021) Day-ahead load probability density forecasting using monotone composite quantile regression neural network and kernel density estimation. Electric Power Systems Research 201, pages 107551.
Crossref
Crossref
Mingming Yang & Songhua Xu. (2021) A novel deep quantile matrix completion model for top-N recommendation. Knowledge-Based Systems 228, pages 107302.
Crossref
Crossref
S. R. Jantre, S. Bhattacharya & T. Maiti. (2021) Quantile Regression Neural Networks: A Bayesian Approach. Journal of Statistical Theory and Practice 15:3.
Crossref
Crossref
Mingyao Ai, Fei Wang, Jun Yu & Huiming Zhang. (2021) Optimal subsampling for large-scale quantile regression. Journal of Complexity 62, pages 101512.
Crossref
Crossref
Georges Bresson, Guy Lacroix & Mohammad Arshad Rahman. (2020) Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada. Empirical Economics 60:1, pages 227-259.
Crossref
Crossref
Ying Cao & Zuo-Jun Max Shen. (2019) Quantile forecasting and data-driven inventory management under nonstationary demand. Operations Research Letters 47:6, pages 465-472.
Crossref
Crossref
Mohammad Arshad Rahman & Angela Vossmeyer. 2019. Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B. Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B
157
191
.
Marco Geraci. (2019) Additive Quantile Regression for Clustered Data with an Application to Children's Physical Activity. Journal of the Royal Statistical Society Series C: Applied Statistics 68:4, pages 1071-1089.
Crossref
Crossref
Marco Geraci. (2019) Modelling and estimation of nonlinear quantile regression with clustered data. Computational Statistics & Data Analysis 136, pages 30-46.
Crossref
Crossref
Yi Wang, Ning Zhang, Yushi Tan, Tao Hong, Daniel S. Kirschen & Chongqing Kang. (2019) Combining Probabilistic Load Forecasts. IEEE Transactions on Smart Grid 10:4, pages 3664-3674.
Crossref
Crossref
Alex J. Cannon. (2018) Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network, with application to rainfall extremes. Stochastic Environmental Research and Risk Assessment 32:11, pages 3207-3225.
Crossref
Crossref
L. Alfredo Fernandez-Jimenez, Sonia Terreros-Olarte, Montserrat Mendoza-Villena, Eduardo Garcia-Garrido, Enrique Zorzano-Alba, Pedro M. Lara-Santillan, Pedro J. Zorzano-Santamaria & Alberto Falces. (2017) Day-Ahead Probabilistic Photovoltaic Power Forecasting Models Based on Quantile Regression Neural Networks. Day-Ahead Probabilistic Photovoltaic Power Forecasting Models Based on Quantile Regression Neural Networks.
Richard Blundell, Joel Horowitz & Matthias Parey. (2017) Nonparametric Estimation of a Nonseparable Demand Function under the Slutsky Inequality Restriction. The Review of Economics and Statistics 99:2, pages 291-304.
Crossref
Crossref
Mohammad Arshad Rahman. (2016) Bayesian Quantile Regression for Ordinal Models. Bayesian Analysis 11:1.
Crossref
Crossref
Andrea C. EnzingerBaohui ZhangDeborah SchragHolly G. Prigerson. (2015) Outcomes of Prognostic Disclosure: Associations With Prognostic Understanding, Distress, and Relationship With Physician Among Patients With Advanced Cancer. Journal of Clinical Oncology 33:32, pages 3809-3816.
Crossref
Crossref
Francesca Giambona & Mariano Porcu. (2015) Student background determinants of reading achievement in Italy. A quantile regression analysis. International Journal of Educational Development 44, pages 95-107.
Crossref
Crossref
Cristina Davino, Marilena Furno & Domenico Vistocco. 2014. Quantile Regression. Quantile Regression
22
63
.
Y. Andriyana, I. Gijbels & A. Verhasselt. (2014) P-splines quantile regression estimation in varying coefficient models. TEST 23:1, pages 153-194.
Crossref
Crossref
Fang Chen & Micheline Chalhoub-Deville. (2013) Principles of quantile regression and an application. Language Testing 31:1, pages 63-87.
Crossref
Crossref
Alan A. Lew & Pin T. Ng. (2011) Using Quantile Regression to Understand Visitor Spending. Journal of Travel Research 51:3, pages 278-288.
Crossref
Crossref
Alex J. Cannon. (2011) Quantile regression neural networks: Implementation in R and application to precipitation downscaling. Computers & Geosciences 37:9, pages 1277-1284.
Crossref
Crossref
Wang Rong, Tang Xiao-wo & Pan Jing-ming. (2010) Analysis of differences of the consumption of mobile voice service based on quantile regression model. Analysis of differences of the consumption of mobile voice service based on quantile regression model.
Colin Chen & Keming Yu. (2008) Automatic Bayesian quantile regression curve fitting. Statistics and Computing 19:3, pages 271-281.
Crossref
Crossref
Pin Ng & Martin Maechler. (2016) A fast and efficient implementation of qualitatively constrained quantile smoothing splines. Statistical Modelling 7:4, pages 315-328.
Crossref
Crossref
Ujjwal Singh, Petr Maca, Martin Hanel, Yannis Markonis, Rama Rao Nidamanuri, Sadaf Nasreen, Johanna Ruth Blöcher, Filip Strnad, Jirl Vorel, Lubomir Riha & Akhilesh Singh Raghubanshi. (2022) Hybrid Multi-Model Ensemble Learning for Reconstructing Gridded Runoff of Europe for 500 Years. SSRN Electronic Journal.
Crossref
Crossref
Mohammad Arshad Rahman & Prajual Maheshwari. (2021) bqror: An R Package for Bayesian Quantile Regression in Ordinal Models. SSRN Electronic Journal.
Crossref
Crossref