35 citations · 95 across the 23 of their papers we have counts for
29 papers
Exploring the big data paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS)
Youqi Yang, Walter Dempsey, Peisong Han +4
Selection bias poses a challenge to statistical inference validity in non-probability surveys. This study compared estimates of the first-dose COVID-19 vaccination rates among Indi…
StabJGL: a stability approach to sparsity and similarity selection in multiple network reconstruction
Camilla Lingjærde, Sylvia Richardson
In recent years, network models have gained prominence for their ability to capture complex associations. In statistical omics, networks can be used to model and study the function…
Bayesian outcome-guided multi-view mixture models with applications in molecular precision medicine
Paul D. W. Kirk, Filippo Pagani, Sylvia Richardson
Clustering is commonly performed as an initial analysis step for uncovering structure in 'omics datasets, e.g. to discover molecular subtypes of disease. The high-throughput, high-…
Scalable Multiple Network Inference with the Joint Graphical Horseshoe
Camilla Lingjærde, Benjamin P. Fairfax, Sylvia Richardson +1
Network models are useful tools for modelling complex associations. If a Gaussian graphical model is assumed, conditional independence is determined by the non-zero entries of the…
Structural randomised selection
Fan Wang, Sylvia Richardson, Steven M. Hill
An important problem in the analysis of high-dimensional omics data is to identify subsets of molecular variables that are associated with a phenotype of interest. This requires ad…
On randomized sketching algorithms and the Tracy-Widom law
Daniel Ahfock, William J. Astle, Sylvia Richardson
There is an increasing body of work exploring the integration of random projection into algorithms for numerical linear algebra. The primary motivation is to reduce the overall com…