Results 51 to 60 of about 113,685 (321)
Disease Mapping via Negative Binomial Regression M-quantiles [PDF]
We introduce a semi-parametric approach to ecological regression for disease mapping, based on modelling the regression M-quantiles of a Negative Binomial variable. The proposed method is robust to outliers in the model covariates, including those due to
Chambers, Ray +2 more
core +1 more source
Stunting is one of the national health problems in Indonesia, where children experience growth failure. This study aims to construct a model for the classification of height gain of stunting toddlers in West Sumatra Province using the Bayesian binary ...
Cintya Mukti +2 more
doaj +1 more source
Risk measurement of oil price based on Bayesian nonlinear quantile regression model
Oil price forecasting is one of the most challenging issues since it is noisy, non-stationary, and chaotic. In this paper, we design a Bayesian Nonlinear Quantile method consisting of a Threshold Improved model and an Adaptive MCMC model to improve ...
Jian Zhu +3 more
doaj +1 more source
Regression Adjustment for Noncrossing Bayesian Quantile Regression [PDF]
A two-stage approach is proposed to overcome the problem in quantile regression, where separately fitted curves for several quantiles may cross. The standard Bayesian quantile regression model is applied in the first stage, followed by a Gaussian process regression adjustment, which monotonizes the quantile function whilst borrowing strength from ...
Rodrigues, Thais, Fan, Yanan
openaire +2 more sources
Mid‐infrared optoacoustic microscopy (MiROM) acquires lipid‐ and protein‐ associated vibrational contrast in intact fat tissue without dyes, preserving native tissue architecture. Through lateral and axial segmentation, MiROM tracks intrinsic intracellular changes during postnatal remodeling. A quantitative spatial analysis tool (Q‐SAT) maps white‐ and
Myeongseop Kim +7 more
wiley +1 more source
Quantile regression with group lasso for classification [PDF]
Applications of regression models for binary response are very common and models specific to these problems are widely used. Quantile regression for binary response data has recently attracted attention and regularized quantile regression methods have ...
A Belloni +41 more
core +1 more source
This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia and explore the correlation between accident severity levels and heterogeneity attributed to unobserved factors.
Xuecai Xu, Željko Šarić
doaj +1 more source
A Bayesian Approach to Envelope Quantile Regression
Summary: The enveloping approach employs sufficient dimension-reduction techniques to gain estimation efficiency, and has been used in several multivariate analysis contexts. However, its Bayesian development has been sparse, and the only Bayesian envelope construction is in the context of a linear regression.
Lee*, Minji +2 more
openaire +2 more sources
Multi‐Tissue Genetic Regulation of RNA Editing in Pigs
This study presents the first multi‐tissue map of RNA editing and its genetic regulation in pigs. By integrating RNA editing profiles, edQTL mapping, GWAS, and cross‐species comparisons, this work establishes RNA editing as a distinct regulatory layer linking genetic variation to complex traits, highlighting its functional and evolutionary significance.
Xiangchun Pan +21 more
wiley +1 more source
Fast calibrated additive quantile regression
We propose a novel framework for fitting additive quantile regression models, which provides well calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diverse as those ...
Azzalini A. +11 more
core +1 more source

