Results 61 to 70 of about 3,477,506 (374)

Prediction of composite indicators using locally weighted quantile regression

Nonlinear Analysis, 2018
The main goal of this paper is to improve the existing methods and tools used for solving penalized quantile regression problems. We modified the quantile regression method by implementing the extreme learning machine (ELM) algorithm and features of ...
Jurga Rukšenaitė, Pranas Vaitkus, Povilas Asijavičius   +2 more
doaj   +1 more source

Mycophenolate Mofetil Treatment Reduces the Risk of Treatment Escalation Due to Vascular Complications in Limited Cutaneous Systemic Sclerosis: Emulation of a Target Trial From the Italian Rheumatology Society SPRING Registry

Arthritis Care &Research, EarlyView.
Objective Mycophenolate mofetil (MMF) use in limited cutaneous systemic sclerosis (lcSSc) is relatively uncommon because of the lower fibrotic burden and the predominance of vascular complications. In vitro observations and clinical data from transplanted patients suggest a protective effect of MMF on endothelial function.
Enrico De Lorenzis, Gerlando Natalello, Rossella De Angelis, Lucrezia Verardi, Dilia Giuggioli, Gianluigi Bajocchi, Lorenzo Dagna, Silvia Bellando‐Randone, Giovanni Zanframundo, Rosario Foti, Fabio Cacciapaglia, Giovanna Cuomo, Alarico Ariani, Edoardo Rosato, Gemma Lepri, Francesco Girelli, Valeria Riccieri, Elisabetta Zanatta, Ilaria Cavazzana, Francesca Ingegnoli, Maria De Santis, Giuseppe Murdaca, Giuseppina Abignano, Giorgio Pettiti, Alessandra Della Rossa, Maurizio Caminiti, Annamaria Iuliano, Giovanni Ciano, Lorenzo Beretta, Gianluca Bagnato, Ennio Lubrano, Maria Ilenia De Andres, Alessandro Giollo, Cosimo Bruni, Martina Orlandi, Marco Fornaro, Marta Saracco, Cecilia Agnes, Pier Giacomo Cerasuolo, Gabriella Alonzi, Edoardo Cipolletta, Federica Lumetti, Amelia Spinella, Luca Magnani, Corrado Campochiaro, Giacomo De Luca, Veronica Codullo, Elisa Visalli, Carlo Iandoli, Antonietta Gigante, Greta Pellegrino, Erika Pigatto, Maria‐Grazia Lazzaroni, Franco Franceschini, Elena Generali, Gianna Mennillo, Simone Barsotti, Giuseppa Pagano Mariano, Federica Furini, Licia Vultaggio, Simone Parisi, Clara Lisa Peroni, Gerolamo Bianchi, Enrico Fusaro, Gian Domenico Sebastiani, Marcello Govoni, Salvatore D'Angelo, Franco Cozzi, Fabrizio Conti, Serena Guiducci, Andrea Doria, Carlo Salvarani, Florenzo Iannone, Maria Antonietta D'Agostino, Clodoveo Ferri, Marco Matucci Cerinic, Silvia Laura Bosello, on behalf of the SPRING Italian Registry Collaborators   +77 more
wiley   +1 more source

Empirical likelihood for quantile regression models with response data missing at random

Open Mathematics, 2017
This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random.
Luo S., Pang Shuxia
doaj   +1 more source

Simulation Study The Implementation of Quantile Bootstrap Method on Autocorrelated Error

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2018
Quantile regression is a regression method with the approach of separating or dividing data into certain quantiles by minimizing the number of absolute values from asymmetrical errors to overcome unfulfilled assumptions, including the presence of ...
Ovi Delviyanti Saputri, Ferra Yanuar, Dodi Devianto   +2 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

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

Quantile calculus and censored regression

, 2010
Quantile regression has been advocated in survival analysis to assess evolving covariate effects. However, challenges arise when the censoring time is not always observed and may be covariate-dependent, particularly in the presence of continuously ...
Huang, Yijian
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Applying quantile regression to determine the effects of household characteristics on household saving rates in Vietnam [PDF]

Journal of Asian Business and Economic Studies, 2020
Purpose – The purpose of this paper is to analyse the determinants of the saving behaviour of Vietnamese households and to explore the possible heterogeneity of household saving propensities. Design/methodology/approach – The authors estimate the effects
Thanh Xuan Hua, Guido Erreygers
doaj   +1 more source

EMPIRICAL REGRESSION QUANTILE

Journal of the Operations Research Society of Japan, 1991
Summary: This study proposes a new use of goal programming for empirically estimating a regression quantile hyperplane. The approach can yield regression quantile estimates that are less sensitive to not only non- Gaussian error distributions but also a small sample size than conventional regression quantile methods.
openaire   +2 more sources