Multivariate analyses such as principal component analysis were among the first statistical methods employed to extract information from genetic markers. From their early applications to current ...

Genome-Wide Association Studies (GWAS) have transformed human genetics by identifying thousands of loci associated with complex traits and diseases. Yet, individual GWAS are often underpowered, and ...

The ever-growing genome-wide association studies (GWAS) have revealed widespread pleiotropy. To exploit this, various methods that jointly consider associations of a genetic variant with multiple ...

The goal of this talk is to familiarize those in attendance with some common multivariate methods, such as principal component analysis, factor analysis, Hotelling’s T 2, etc. We’ll try to motivate ...

Abstract: Multivariate Time Series (MTS) forecasting has a wide range of applications in both industry and academia. Recent advances in Spatial-Temporal Graph Neural Network (STGNN) have achieved ...

Methods to Reduce the Dimension of Multivariate Models. (2023). Linear Models for the Prediction of the Genetic Merit of Animals, 123–136. https://doi.org/10.1079 ...

Abstract: Entropy serves as an effective nonlinear dynamic indicator of time series complexity. A number of multivariate entropy methods exist and are effectively used in signal analysis. Existing ...