2026-04-17T03:15:53Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4717092024-11-04T06:48:19Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Jin, Suzanne author Notredame, Cedric author Erb, Ionas author 2023 We propose an estimation procedure for covariation in wide compositional data sets. For compositions, widely-used logratio variables are interdependent due to a common reference. Logratio uncorrelated compositions are linearly independent before the unitsum constraint is imposed. We show how they are used to construct bespoke shrinkage targets for logratio covariance matrices and test a simple procedure for partial correlation estimates on both a simulated and a single-cell gene expression data set. For the underlying counts, different zero imputations are evaluated. The partial correlation induced by the closure is derived analytically. Data and code are available from GitHub. http://hdl.handle.net/2072/471709 Compositional covariance structure Logratio analysis Partial correlation James-Stein shrinkage Compositional covariance shrinkage and regularised partial correlations