An Information Matrix Prior for Bayesian Analysis in Generalized Linear Models with High Dimensional Data.

@article{Gupta2009AnIM,
  title={An Information Matrix Prior for Bayesian Analysis in Generalized Linear Models with High Dimensional Data.},
  author={Mayetri Gupta and Joseph G. Ibrahim},
  journal={Statistica Sinica},
  year={2009},
  volume={19 4},
  pages={
          1641-1663
        }
}
An important challenge in analyzing high dimensional data in regression settings is that of facing a situation in which the number of covariates p in the model greatly exceeds the sample size n (sometimes termed the "p > n" problem). In this article, we develop a novel specification for a general class of prior distributions, called Information Matrix (IM) priors, for high-dimensional generalized linear models. The priors are first developed for settings in which p < n, and then extended to the… CONTINUE READING
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