Higber Order Expansions of the Cumulants and the Modified Normalizing Process of Multi-dimensional Maximum Likelihood Estimator

  • Jonghwa Na (Assistant Professor Department of Statistics Chungbuk National University)
  • Published : 1999.04.01

Abstract

In this paper we derive the higher order expansions of the first four cumulants of multi-dimensional Maximum Likelihood Estimator (MLE) under the general parametric model up to and including terms of order O({{{{ {n }^{-1 } }}}}) Also we obtain the explicit form of the expansion of the normalizing trans formation of multi-dimensional MLE and show that the suggested normalizing process is much better than the normal approximation based on central limit theorem through example.

Keywords

References

  1. Asymptotic Techniques for Use in Statistics Barndorff-Nielsen, O.E.;Cox, D.R.
  2. Revue de I'Institut Internationale de Statistique v.4 Moments and cumulants in the specification of distributions Cornish, E.A.;Fisher, R.A.
  3. Biometrika v.71 Tensor notation and cumulants of polynomials McCullagh, P.
  4. Tensor Methods in Statistics McCullagh, P.
  5. Austral. J. Statist v.25 Cumulants and partition lattices Speed, T.P.
  6. Journal of Computational and Graphical Statistics v.3 Automating the partition of indexes Stafford, J.E.
  7. Biometrika v.80 A symbolic algorithm for studying adjustments to the profile likelihood Stafford, J.E.;Andrews, D.F.
  8. Statistics and Computation v.4 Symbolic computation : A unified approach to studying likelihood Stafford, J.E.;Andrews, D.F.;Wang, Y.
  9. Ann. Math. Statist. v.29 Asymptotic approximations to distributions Wallace, D.L.