Numerical evaluation of methods approximating the distribution of a large quadratic form in normal variables

DOI10.1016/j.csda.2019.05.002OpenAlexW2944236149MaRDI QIDQ2002719

Thomas Lumley, Tong Chen

Publication date: 12 July 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2019.05.002

zbMATH Keywords

computational complexityaccuracyleading-eigenvalue approximationsmall \(p\)-values

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Approximations to statistical distributions (nonasymptotic) (62E17)

Uses Software

• R
• GitHub
• AS 155
• SKAT
• AS 204
• bigQF

Cites Work

• Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
• A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables
• Computing the distribution of quadratic forms: further comparisons between the Liu-Tang-Zhang approximation and exact methods
• The tail of the convolution of densities and its application to a model of HIV-latency time
• On the efficient calculation of a linear combination of chi-square random variables with an application in counting string vacua
• The Analysis of Categorical Data From Complex Sample Surveys: Chi-Squared Tests for Goodness of Fit and Independence in Two-Way Tables
• Algorithm AS 155: The Distribution of a Linear Combination of χ 2 Random Variables
• Miscellanea. Saddlepoint approximations for distributions of quadratic forms in normal variables
• Application of the Method of Mixtures to Quadratic Forms in Normal Variates