High-dimensional statistical testing and covariance analysis constitute a rapidly evolving field that addresses the challenges inherent in analysing datasets where the number of variables often ...

We propose new regression models for parameterizing covariance structures in longitudinal data analysis. Using a novel Cholesky factor, the entries in this decomposition have a moving average and ...

To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful. However, a single two-dimensional ...