Abstract Geographically Weighted Principal Component Analysis (GWPCA) is an extension
of classical PCA to deal with the spatial heterogeneity of geographical data. This …

In the study of brain functional connectivity networks, it is assumed that a network is built
from a data window in which activity is stationary. However, brain activity is non-stationary …

Background Compared to national evaluations, international collaboration projects further
improve accuracies of estimated breeding values (EBV) by building larger reference …

The validity of the Efficient Market Hypothesis (EMH) as an assumption for portfolio
optimization in the Mean–Variance (MV) framework under large scale financial crises is …

Background The accuracy of genomic prediction is partly determined by the size of the
reference population. In Atlantic salmon breeding programs, four parallel populations often …

Background Multi-population genomic prediction can rapidly expand the size of the
reference population and improve genomic prediction ability. Machine learning (ML) …

In beef cattle maternally influenced traits, estimates of direct-maternal genetic correlations (r
dm) are usually reported to be negative. In international evaluations, r dm can differ both …

Many traits of economical relevance in beef cattle are influenced in their phenotypic
expression by the dam. Genetic evaluations of maternally affected traits require to model …

Additive and dominance genetic variances underlying the expression of quantitative traits
are important quantities for predicting short‐term responses to selection, but they are …

Kalman filtering (KF) is widely used in real-time precise point positioning (PPP) systems. The
stochastic models for the dynamic and measurement systems, however, are often …