3 papers
stat.AP2020
BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
Qingyuan Zhao, Nianqiao Ju, Sergio Bacallado +1
The coronavirus disease 2019 (COVID-19) has quickly grown from a regional outbreak in Wuhan, China to a global pandemic. Early estimates of the epidemic growth and incubation perio…
stat.ME2019
Goodness-of-fit testing in high-dimensional generalized linear models
Jana Janková, Rajen D. Shah, Peter Bühlmann +1
We propose a family of tests to assess the goodness-of-fit of a high-dimensional generalized linear model. Our framework is flexible and may be used to construct an omnibus test or…
stat.ME2018
RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding
Rajen D. Shah, Benjamin Frot, Gian-Andrea Thanei +1
In this work we consider the problem of estimating a high-dimensional covariance matrix , given observations of confounded data with covariance , where…