Results 111 to 120 of about 3,477,506 (374)
Using Quantile Regression for Duration Analysis [PDF]
Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the ...
Fitzenberger, Bernd, Wilke, Ralf A.
core
AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification
Econometrics, 2015 Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
doaj +1 more source
Computational study of permeability in cardboard coating layers
AIChE Journal, EarlyView.Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman +6 more
wiley +1 more source
Powerful nonparametric checks for quantile regression [PDF]
, 2014 We address the issue of lack-of-fit testing for a parametric quantile regression. We propose a simple test that involves one-dimensional kernel smoothing, so that the rate at which it detects local alternatives is independent of the number of covariates.
Lavergne, Pascal +2 more
core +4 more sources
Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns
Advanced Intelligent Discovery, EarlyView.Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer +6 more
wiley +1 more source
Corrigendum: Modified quantile regression for modeling the low birth weight
Frontiers in Applied Mathematics and Statistics, 2023 Ferra Yanuar +2 more
doaj +1 more source
Regression for Exploring Rainfall Pattern in Indramayu Regency
Jurnal Ilmu Dasar, 2012 Quantile regression is an important tool for conditional quantiles estimation of a response Y for a given vector of covariates X. It can be used to measure the effect of covariates not only in the center of a distribution, but also in the upper and lower
Anik Djuraidah, Aji Hamim Wigena
doaj
REGRESI KUANTIL MEDIAN UNTUK MENGATASI HETEROSKEDASTISITAS PADA ANALISIS REGRESI
E-Jurnal Matematika, 2013 In regression analysis, the method used to estimate the parameters is Ordinary Least Squares (OLS). The principle of OLS is to minimize the sum of squares error. If any of the assumptions were not met, the results of the OLS estimates are no longer best,
IDA AYU PRASETYA UTHAMI +2 more
doaj +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone +11 more
wiley +1 more source