Results 91 to 100 of about 2,633 (230)
Bayesian inverse ensemble forecasting for COVID‐19
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source
A goodness‐of‐fit test for regression models with discrete outcomes
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source
"On the Effectiveness of Monetary Policy and Fiscal Policy" [PDF]
Within the framework of macroeconomic policy and theory over the past twenty years or so, a major shift has occurred regarding the relative importance given of monetary policy versus fiscal policy. The former has gained considerably in stature, while the
Malcolm Sawyer, Philip Arestis
core
Jackknife bias‐corrected variance estimation for the generalized regression estimator
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley +1 more source
A partial envelope approach for modelling multivariate spatial‐temporal data
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja +3 more
wiley +1 more source
Nonlinear permuted Granger causality
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley +1 more source
Residential Segregation in General Equilibrium [PDF]
This paper studies the causes and consequences of racial segregation using a new general equilibrium model that treats neighborhood compositions as endogenous.
Kim Rueben +2 more
core
Traditional dosing strategies often rely on a “one‐size‐fits‐all” paradigm, assuming an “average” patient with typical demographic and pharmacological characteristics. In reality, this often overlooks existing between‐patient variability and can lead to suboptimal drug exposure or toxicity. This issue is especially pronounced in pediatric patients, who
Zachary L. Taylor +12 more
wiley +1 more source
Quenching the Hubbard Model: Comparison of Nonequilibrium Green's Function Methods
ABSTRACT We benchmark nonequilibrium Green's function (NEGF) approaches for interaction quenches in the half‐filled Fermi–Hubbard model in one and two dimensions. We compare fully self‐consistent two‐time Kadanoff–Baym equations (KBE), the generalized Kadanoff–Baym ansatz (GKBA), and the recently developed NEGF‐based quantum fluctuations approach (NEGF‐
Jan‐Philip Joost +3 more
wiley +1 more source
ABSTRACT Advances in spectral cytometry instrumentation and fluorescent reagents have led to the possibility of ultra‐high‐parameter panels exceeding 50 colors. However, panel size is limited in practice by unmixing‐dependent spreading (UDS), a phenomenon which leads to a progressive deterioration of unmixed signal‐to‐noise ratios in panels that ...
Peter L. Mage +2 more
wiley +1 more source

