Results 51 to 60 of about 15,953 (268)
Penalized additive regression for space-time data: a Bayesian perspective [PDF]
, 2003 We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective.
Fahrmeir, Ludwig +2 more
core +3 more sources
A time series analysis of meteorological factors and hospital outpatient admissions for cardiovascular disease in the Northern district of Guizhou Province, China [PDF]
Brazilian Journal of Medical and Biological Research, 2014 Findings on the effects of weather on health, especially the effects of ambient temperature on overall morbidity, remain inconsistent. We conducted a time series study to examine the acute effects of meteorological factors (mainly air temperature) on ...
Y. Jie +4 more
doaj +3 more sources
Maximal Associated Regression: A Nonlinear Extension to Least Angle Regression
IEEE Access, 2021 This paper proposes Maximal Associated Regression (MAR), a novel algorithm that performs forward stage-wise regression by applying nonlinear transformations to fit predictor covariates.
Sanush K. Abeysekera +3 more
doaj +1 more source
Variable Selection and Model Choice in Geoadditive Regression Models [PDF]
, 2007 Model choice and variable selection are issues of major concern in practical regression analyses. We propose a boosting procedure that facilitates both tasks in a class of complex geoadditive regression models comprising spatial effects, nonparametric ...
Hothorn, Torsten +2 more
core +1 more source
Advanced Healthcare Materials, EarlyView.A two‐phase workflow (OFAT screening followed by central composite design) maps how processing variables tune PFCE‐PLGA nanoparticle size, dispersity, surface charge, loading, and 19F‐MRI signal. In situ, time‐resolved synchrotron SAXS tracks albumin‐corona growth on intact dispersions and reveals PFCE‐dependent adsorption pathways.
Joice Maria Joseph +11 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Semiparametric estimation for a class of time-inhomogenous diffusion processes [PDF]
, 2009 Copyright @ 2009 Institute of Statistical Science, Academia SinicaWe develop two likelihood-based approaches to semiparametrically estimate a class of time-inhomogeneous diffusion processes: log penalized splines (P-splines) and the local log-linear ...
Li, M, Wang, H, Yu, K, Yu, Y
core
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
BMC Medical Research Methodology, 2019 Background The analysis of twin data presents a unique challenge. Second-born twins on average weigh less than first-born twins and have an elevated risk of perinatal mortality.
Muhammad Abu Shadeque Mullah +2 more
doaj +1 more source
Trend Estimation with Penalized Splines as Mixed Models for Series with Structural Breaks [PDF]
, 2014 On purpose to extract trend and cycle from a time series many competing techniques have been developed. The probably most prevalent is the Hodrick Prescott filter. However this filter suffers from diverse shortcomings, especially the subjective choice of
Blöchl, Andreas
core +2 more sources