Statistical methods for variable selection and model estimation are crucial in data analysis, particularly when dealing with complex datasets that contain numerous variables. These methods help ...
A recent study by Romina Wild and SISSA Professor Alessandro Laio, along with Felix Wodaczek, Vittorio Del Tatto, and Bingqing Cheng, published in the journal Nature Communications, introduces a new ...
Abstract: This paper describes an approach to the analysis of linear variable networks which is essentially an extension of the frequency analysis techniques commonly used in connection with fixed ...
Determining the covariance of two variables is called covariance analysis. For example ... “Portfolio Selection.” The Journal of Finance, vol. 7, no. 1, March 1952, pp. 77-91.