Results 71 to 80 of about 11,485 (217)

A novel method for fractal-fractional differential equations

Alexandria Engineering Journal, 2022
We consider the reproducing kernel Hilbert space method to construct numerical solutions for some basic fractional ordinary differential equations (FODEs) under fractal fractional derivative with the generalized Mittag–Leffler (M-L) kernel.
Nourhane Attia, Ali Akgül, Djamila Seba, Abdelkader Nour, Jihad Asad   +4 more
doaj  

A Recursive Model Approach to Include Epigenetic Effects in Genetic Evaluations Using Simulated DNA Methylation Effects

Journal of Animal Breeding and Genetics, EarlyView.
ABSTRACT The advancement of epigenetics has highlighted DNA methylation as an intermediate‐omic influencing gene regulation and phenotypic expression. With emerging technologies enabling the large‐scale and affordable capture of methylation data, there is growing interest in integrating this information into genetic evaluation models for animal ...
Adrián López‐Catalina, Mohamed Ragab, Antonio Reverter, Oscar González‐Recio   +3 more
wiley   +1 more source

Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression

Journal of Applied Mathematics, 2012
We study learning algorithms generated by regularization schemes in reproducing kernel Hilbert spaces associated with an ϵ-insensitive pinball loss. This loss function is motivated by the ϵ-insensitive loss for support vector regression and the pinball ...
Dao-Hong Xiang, Ting Hu, Ding-Xuan Zhou
doaj   +1 more source

Numerical solution of fractional differential equations with temporal two-point BVPs using reproducing kernal Hilbert space method

AIMS Mathematics, 2021
In this paper, the reproducing kernel Hilbert space method had been extended to model a numerical solution with two-point temporal boundary conditions for the fractional derivative in the Caputo sense, convergent analysis and error bounds are discussed ...
Yassamine Chellouf, Banan Maayah, Shaher Momani , Ahmad Alawneh, Salam Alnabulsi   +4 more
doaj   +1 more source

A Reproducing Kernel Hilbert Space Approach to Functional Linear Regression [PDF]

, 2010
We study in this paper a smoothness regularization method for functional linear regression and provide a unified treatment for both the prediction and estimation problems.
M. Yuan, Tommaso Cai
semanticscholar   +1 more source

Global sensitivity analysis of integrated assessment models with multivariate outputs

Risk Analysis, EarlyView.
Abstract Risk assessments of complex systems are often supported by quantitative models. The sophistication of these models and the presence of various uncertainties call for systematic robustness and sensitivity analyses. The multivariate nature of their response challenges the use of traditional approaches.
Leonardo Chiani, Emanuele Borgonovo, Elmar Plischke, Massimo Tavoni   +3 more
wiley   +1 more source

Numerical solvability of generalized Bagley–Torvik fractional models under Caputo–Fabrizio derivative

Advances in Difference Equations, 2021
This paper deals with the generalized Bagley–Torvik equation based on the concept of the Caputo–Fabrizio fractional derivative using a modified reproducing kernel Hilbert space treatment.
Shatha Hasan, Nadir Djeddi, Mohammed Al-Smadi, Shrideh Al-Omari, Shaher Momani, Andreea Fulga   +5 more
doaj   +1 more source

Stein's method of moments

Scandinavian Journal of Statistics, EarlyView.
Abstract Stein operators allow one to characterize probability distributions via differential operators. Based on these characterizations, we develop a new method of point estimation for marginal parameters of strictly stationary and ergodic processes, which we call Stein's Method of Moments (SMOM). These SMOM estimators satisfy the desirable classical
Bruno Ebner, Adrian Fischer, Robert E. Gaunt, Babette Picker, Yvik Swan   +4 more
wiley   +1 more source

VECTOR VALUED REPRODUCING KERNEL HILBERT SPACES AND UNIVERSALITY [PDF]

Analysis and Applications, 2010
This paper is devoted to the study of vector valued reproducing kernel Hilbert spaces. We focus on two aspects: vector valued feature maps and universal kernels. In particular, we characterize the structure of translation invariant kernels on abelian groups and we relate it to the universality problem.
E. De Vito, Claudio Carmeli, Alessandro Toigo, Veronica Umanità, Veronica Umanità   +4 more
openaire   +4 more sources

Do not benchmark phenomic prediction against genomic prediction accuracy

The Plant Phenome Journal, Volume 8, Issue 1, December 2025.
Abstract Phenomic selection is a new paradigm in plant breeding that uses high‐throughput phenotyping technologies and machine learning models to predict traits of new individuals and make selections. This can allow breeders to evaluate more plants in higher throughput more accurately, resulting in faster rates of gain and reduced labor costs. However,
Fangyi Wang, Mitchell J. Feldmann, Daniel E. Runcie   +2 more
wiley   +1 more source