Results 61 to 70 of about 2,542,650 (299)
Regression on Quantile Residual Life [PDF]
SummaryA time‐specific log‐linear regression method on quantile residual lifetime is proposed. Under the proposed regression model, any quantile of a time‐to‐event distribution among survivors beyond a certain time point is associated with selected covariates under right censoring.
Jung, Sin-Ho +2 more
openaire +3 more sources
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong +7 more
wiley +1 more source
Empirical likelihood for quantile regression models with response data missing at random
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
Quantity quantiles linear regression [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Paolo Radaelli, Michele Zenga
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A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai +3 more
wiley +1 more source
bayesQR: A Bayesian Approach to Quantile Regression
After its introduction by Koenker and Basset (1978), quantile regression has become an important and popular tool to investigate the conditional response distribution in regression. The R package bayesQR contains a number of routines to estimate quantile
Dries F. Benoit, Dirk Van den Poel
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Quantile cointegrating regression [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Nonparametric estimation of an additive quantile regression model [PDF]
This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n^{-r/(2+10)} when ...
Joel L. Horowitz +5 more
core +1 more source
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen +7 more
wiley +1 more source
Censored Quantile Regression Redux
Quantile regression for censored survival (duration) data offers a more flexible alternative to the Cox proportional hazard model for some applications. We describe three estimation methods for such applications that have been recently incorporated into ...
Roger Koenker
doaj

