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 ...
This is a brief description for the experiments of the USSP algorithm project. This project contains all the programs used in Paper "Stable Subsampling under Model Misspecification and Data Shift", ...
Abstract: NADA is a synthetic dataset of 1,500,000 (128x128 pixels) images of geometric shapes with non-elementary multivariate parameter distributions designed to benchmark and test novel ...
Abstract: Multivariate time series forecasting estimates future development by capturing variable relationships and constructing temporal regular, which is widely used in many scenarios, including ...
We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for ...
cov1Para: Linear shrinkage towards one-parameter matrix; all the variances are the same, all the covariances are zero. See Ledoit and Wolf (2004b). cov2Para: Linear shrinkage towards two-parameter ...
Figure 1: Hierarchical model schematic; information from all base-level models is communicated to a top-level model through their respective matrices (T j) into a consensus matrix R. R is used to ...
VAR models analyse and predict multivariate time series data, unlike univariate autoregressive models. These models are particularly useful in fields such as economics and weather forecasting. VAR ...
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