Smoothness of Gaussian Conditional Independence Models

@inproceedings{Drton2010SmoothnessOG,
  title={Smoothness of Gaussian Conditional Independence Models},
  author={Mathias Drton and Han Xiao},
  year={2010}
}
Conditional independence in a multivariate normal (or Gaussian) distribution is characterized by the vanishing of subdeterminants of the distribution’s covariance matrix. Gaussian conditional independence models thus correspond to algebraic subsets of the cone of positive definite matrices. For statistical inference in such models it is important to know whether or not the model contains singularities. We study this issue in models involving up to four random variables. In particular, we give… CONTINUE READING

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