Two approaches to approximating sums of chisquareds
Compares Satterthwaite, Liu, and leading-term approximations for tail probabilities of weighted sums of chi-squared variables in high-dimensional genomic data.
Compares Satterthwaite, Liu, and leading-term approximations for tail probabilities of weighted sums of chi-squared variables in high-dimensional genomic data.
Analyzes the accuracy of a leading eigenvalue approximation for quadratic forms in Gaussian variables, comparing it to traditional methods.
Explores methods for computing tail probabilities of linear combinations of chi-squared variables, focusing on applications in genetics with large datasets.
Explores computational challenges of large quadratic forms in genomics, focusing on eigenvalue approximations for high-dimensional statistical tests like SKAT.