ANCILLARY STATISTICS: A REVIEW

By Malay Ghosh, Nancy Reid, Donald Fraser. 2010

81 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6c489711e92a98f010c04ce13e6877102846b499

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Peter Buhlmann
2. Sara A. van de Geer
3. Nicolai Meinshausen
4. Jan Peters
5. Panayiota Constantinou
6. Cun-Hui Zhang
7. Martin J. Wainwright
8. Tong Zhang

Citations in the corpus

• Extended Conditional Independence and Applications in Causal Inference (2015, methodology): “Ancillary statistics can be used to recover information lost by reducing the data to the maximum likelihood estimate [35].”
• High-dimensional inference in misspecified linear models (2015, background): “In other words, conditioning on the covariates is only justifiable if the model is correct and in that case, it is a well established principle in the low-dimensional case with p < n based on an ancillarity argument [4, 16].”
• Diagnostics of prior-data agreement in applied Bayesian analysis (2008, background): “A difficulty however occurs when a component U of T is an ancillary statistic, namely a statistic whose distribution does not depend on θ [33].”