A New Unit‐Lindley Mixed‐Effects Model With an Application to Electricity Access Data
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT This paper introduces a novel unit‐Lindley mixed‐effects model (NULMM) within the generalized linear mixed model (GLMM) framework, designed for analyzing correlated response variables bounded within the unit interval. Parameter estimation was conducted via maximum likelihood, using Laplace approximation and adaptive Gaussian‐ Hermite ...
Nirajan Bam +2 more
wiley +1 more source
Knot data analysis using multiscale Gauss link integral. [PDF]
Proc Natl Acad Sci U S AShen L +5 more
europepmc +1 more source
Physics‐Based Machine Learning for Modeling Cyclic Damage Evolution
PAMM, Volume 26, Issue 1, March 2026.ABSTRACT Accurate modeling of cyclic damage evolution is essential for predicting the long‐term performance and durability of engineering materials and structures. Traditional simulation‐based approaches, while physically rigorous, are computationally expensive, especially under complex loading histories.
Elsayed S. Elsayed +2 more
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Improved prediction and flagging of extreme random effects for non-Gaussian outcomes using weighted methods. [PDF]
BiometricsNeuhaus J, McCulloch C, Boylan R.
europepmc +1 more source
Sums of Gauss, Jacobi, and Jacobsthal
Journal of Number Theory, 1979 Berndt, Bruce C, Evans, Ronald J
openaire +2 more sources
Methods Based on Polynomial Chaos for Quadratic Delay Differential Equations With Random Parameters
PAMM, Volume 26, Issue 1, March 2026.ABSTRACT We consider systems of delay differential equations (DDEs), including a single delay and a quadratic right‐hand side. In a system, parameters are replaced by random variables to perform an uncertainty quantification. Thus the solution of the DDEs becomes a random process, which can be represented by a series of the generalised polynomial chaos.
Roland Pulch
wiley +1 more source
Exact Expressions for Kullback-Leibler Divergence for Multivariate and Matrix-Variate Distributions. [PDF]
Entropy (Basel)Nawa V, Nadarajah S.
europepmc +1 more source
A Generalization Error Bound of Physics‐Informed Neural Networks for Ecological Diffusion Models
Stat, Volume 15, Issue 1, March 2026.ABSTRACT Ecological diffusion equations (EDEs) are partial differential equations (PDEs) that model spatiotemporal dynamics, often applied to wildlife diseases. Derived from ecological mechanisms, EDEs are useful for forecasting, inference, and decision‐making, such as guiding surveillance strategies for wildlife diseases.
Juan Francisco Mandujano Reyes +4 more
wiley +1 more source
Optimal Choice of the Regularization Parameter for Direct Identification of Polymers Relaxation Time and Frequency Spectra. [PDF]
Polymers (Basel)Stankiewicz A, Bojanowska M.
europepmc +1 more source
Hybrid kernels integrating genomic and multispectral data improve wheat genomic prediction accuracy
The Plant Genome, Volume 19, Issue 1, March 2026.Abstract Genomic selection (GS) is transforming plant breeding by enabling more accurate and efficient identification of superior genotypes. However, its practical implementation remains challenging, as achieving high prediction accuracy is critical for its success. Several factors—including sample size, the degree of relatedness among individuals, and
Osval A. Montesinos‐López +8 more
wiley +1 more source