A simplified proof of a cosmological singularity theorem. [PDF]
Galloway GJ, Ling E.
europepmc +1 more source
Asymptotic properties of cross‐classified sampling designs
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source
Transfer Learning for Moderate-Dimensional Ridge-Regularized Robust Linear Regression. [PDF]
Lyu L, Guo X, Liu Z.
europepmc +1 more source
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
Quantum algorithms for viscosity solutions to nonlinear Hamilton-Jacobi equations based on an entropy penalization method. [PDF]
Jin S, Liu N.
europepmc +1 more source
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
The C 0 -inextendibility of some spatially flat FLRW spacetimes. [PDF]
Ling E.
europepmc +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
Evolution of a trait distributed over a large fragmented population: propagation of chaos meets adaptive dynamics. [PDF]
Lambert A +3 more
europepmc +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

