Corpus ID: 88519358

Bernstein - von Mises Theorem for growing parameter dimension

@article{Spokoiny2013BernsteinV,
  title={Bernstein - von Mises Theorem for growing parameter dimension},
  author={V. Spokoiny},
  journal={arXiv: Statistics Theory},
  year={2013}
}

V. Spokoiny

Published 2013

Mathematics

arXiv: Statistics Theory

This paper revisits the prominent Fisher, Wilks, and Bernstein -- von Mises (BvM) results from different viewpoints. Particular issues to address are: nonasymptotic framework with just one finite sample, possible model misspecification, and a large parameter dimension. In particular, in the case of an i.i.d. sample, the mentioned results can be stated for any smooth parametric family provided that the dimension \(p \) of the parameter space satisfies the condition "\(p^{2}/n \) is small" for… CONTINUE READING

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