MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records. [PDF]
Wang Z, Liu T, Yao B.
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
Critical impact of automobile industry with advanced decision support system and Aczél-Alsina Hammy mean operators. [PDF]
Hussain A, Ullah K, Ali Z, Pamucar D.
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
A Random Differential Equation Approach for Modeling the Growth of Microalgae in Photobioreactors. [PDF]
Andreu-Vilarroig C +4 more
europepmc +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
The Capacity Gains of Gaussian Channels with Unstable Versus Stable Autoregressive Noise. [PDF]
Charalambous CD +3 more
europepmc +1 more source
An approximate Gauss mean value theorem [PDF]
openaire +3 more sources
Non‐negative Gaussian estimation of variance components in random effects models
Abstract When used to estimate variance components (VCs), confidence intervals (CIs) can be truncated at zero, have a point estimate not in the quoted CI, be empty with positive probability, or be all‐inclusive. This is because they have conflicting dual roles, since they are considered to cover the parameter with a specified probability while also ...
André Plante, Michael Plante
wiley +1 more source
Nonparametric Tests for Exponentiality Against IFRA Alternatives Based on Cumulative Extropy Measures. [PDF]
Alqefari AA.
europepmc +1 more source

