Results 151 to 160 of about 137,194 (317)
Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure [PDF]
Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the
Victor Chernozhukov +2 more
core
Advanced Intelligent Systems, EarlyView.This work presents a bio‐inspired computing framework for Parkinson's disease analog recognition using electroencephalogram signals. Temporally encoded EEG features stimulate a mycelium‐inspired memristive reservoir, where disease‐related patterns emerge through physical spatiotemporal dynamics.
Ioannis K. Chatzipaschalis +5 more
wiley +1 more source
Modeling Quantile Dependence: A New Look at the Money-Output Relationship [PDF]
Do money supply shocks influence output growth asymmetrically? At different levels of output growth, would the influence of the same monetary policy stance vary?
Nicholas C.S. Sim
core
Advanced Intelligent Systems, EarlyView.Complex dynamics, often avoided in electromechanical design, can enhance soft robotics. We develop durable magnetic soft actuators operating in tunable dynamic regimes, enabling random number generation, stochastic computing, and time‐series prediction.
Eduardo Sergio Oliveros‐Mata +14 more
wiley +1 more source
Housing as Asset‐Based Welfare in Australia: An Investigation Through a Consumption Lens
Australian Journal of Social Issues, EarlyView.ABSTRACT Housing asset‐based welfare has long been a key component of Australia's social policy. This resonates with a parallel literature identifying a trade‐off between homeownership and the size of nations' welfare states, wherein owner‐occupiers in smaller welfare states tend to come to rely on housing wealth to meet many of their welfare needs ...
Gavin A. Wood +3 more
wiley +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
Multimorbidity and Associations with Cognition and Alzheimer's Disease Biomarkers
Annals of Neurology, EarlyView.Objective Multimorbidity, the coexistence of 2 or more chronic conditions, has been linked to cognitive aging and Alzheimer's disease (AD) and AD‐related dementias, yet the mechanisms remain unclear. We aimed to examine the associations of multimorbidity with cognition and biomarkers across multiple mechanistic pathways.
Xiaqing Jiang +45 more
wiley +1 more source
Archaeological Prospection, EarlyView.ABSTRACT Burial mounds are key elements of Mediterranean funerary landscapes, but in intensively cultivated coastal plains their low‐relief expression is easily obscured by ploughing, levelling and rapidly changing surface conditions, making single‐date observations unreliable.
Salvatore Polverino +2 more
wiley +1 more source
Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors [PDF]
We consider nonparametric estimation of the conditional qth quantile for stationary time series. We deal with stationary time series with strong time dependence and heavy tails under the setting of random design.
Toshio Honda
core
Per‐ and Polyfluoroalkyl Substances and Knee Osteoarthritis: Data From the Osteoarthritis Initiative
Arthritis &Rheumatology, EarlyView.Objective To examine whether concentrations of specific per‐ and polyfluoroalkyl substances (PFAS) and a mixture of PFAS relate to incident knee osteoarthritis (KOA) and knee pain progression. Methods Among a case‐cohort sample from the OA Initiative (n = 1,878), we examined associations of serum concentrations of eight PFAS with odds of developing ...
Jeffrey B. Driban +14 more
wiley +1 more source