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pro vyhledávání: '"Goudie, Robert"'
It is of scientific interest to identify essential biomarkers in biological processes underlying diseases to facilitate precision medicine. Factor analysis (FA) has long been used to address this goal: by assuming latent biological pathways drive the
Externí odkaz:
http://arxiv.org/abs/2408.08771
The increasing availability of high-dimensional, longitudinal measures of gene expression can facilitate understanding of biological mechanisms, as required for precision medicine. Biological knowledge suggests that it may be best to describe complex
Externí odkaz:
http://arxiv.org/abs/2307.02781
When complex Bayesian models exhibit implausible behaviour, one solution is to assemble available information into an informative prior. Challenges arise as prior information is often only available for the observable quantity, or some model-derived
Externí odkaz:
http://arxiv.org/abs/2303.08528
Autor:
Liu, Yang, Goudie, Robert J. B.
Standard Bayesian inference can build models that combine information from various sources, but this inference may not be reliable if components of a model are misspecified. Cut inference, as a particular type of modularized Bayesian inference, is an
Externí odkaz:
http://arxiv.org/abs/2211.03274
A challenge for practitioners of Bayesian inference is specifying a model that incorporates multiple relevant, heterogeneous data sets. It may be easier to instead specify distinct submodels for each source of data, then join the submodels together.
Externí odkaz:
http://arxiv.org/abs/2111.11566
Autor:
Nicholson, George, Blangiardo, Marta, Briers, Mark, Diggle, Peter J., Fjelde, Tor Erlend, Ge, Hong, Goudie, Robert J. B., Jersakova, Radka, King, Ruairidh E., Lehmann, Brieuc C. L., Mallon, Ann-Marie, Padellini, Tullia, Teh, Yee Whye, Holmes, Chris, Richardson, Sylvia
We present "interoperability" as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of princi
Externí odkaz:
http://arxiv.org/abs/2109.13730
Autor:
Liu, Yang, Goudie, Robert J. B.
Geographically weighted regression (GWR) models handle geographical dependence through a spatially varying coefficient model and have been widely used in applied science, but its general Bayesian extension is unclear because it involves a weighted lo
Externí odkaz:
http://arxiv.org/abs/2106.00996
The case-cohort study design bypasses resource constraints by collecting certain expensive covariates for only a small subset of the full cohort. Weighted Cox regression is the most widely used approach for analysing case-cohort data within the Cox m
Externí odkaz:
http://arxiv.org/abs/2007.12974
Autor:
Liu, Yang, Goudie, Robert J. B.
Bayesian modelling enables us to accommodate complex forms of data and make a comprehensive inference, but the effect of partial misspecification of the model is a concern. One approach in this setting is to modularize the model, and prevent feedback
Externí odkaz:
http://arxiv.org/abs/2006.01584
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