Multivariate normal approximation of the maximum likelihood estimator via the delta method

Billingsley, P. Statistical Methods in Markov Chains. Ann. Math. Stat. 𝟑𝟐 \mathbf{32} (1961), 12–40

1961

Earlier work this paper cites.

Cox, D. R. and Snell, E. J. A General Definition of Residuals. J. Roy. Stat. Soc. B Met. 𝟑𝟎 \mathbf{30} (1968), 248–275

1968

Earlier work this paper cites.

Mäkeläinen, T., Schmidt, T. K. and Styan, G. P. H. On the existence and uniqueness of the maximum likelihood estimate of a vector-valued parameter in fixed size samples. Ann. Stat. 𝟗 \mathbf{9} (1981), 758–767

1981

Earlier work this paper cites.

Davison A. C. Statistical Models

2008

Earlier work this paper cites.

Winkelbauer, A. Moments and absolute moments of the normal distribution. arXiv:1209.4340, 2012

Original

2012

Cited alongside, same era.

Anastasiou, A. Assessing the multivariate normal approximation of the maximum likelihood estimator from high-dimensional, heterogeneous data. arXiv:1510.03679, 2015

Original

2015

Cited alongside, same era.

Gaunt, R. E. Rates of Convergence in Normal Approximation Under Moment Conditions Via New Bounds on Solutions of the Stein Equation. J. Theoret. Probab. 𝟐𝟗 \mathbf{29} (2016), 231-247

2016

Cited alongside, same era.

Gaunt, R. E. and Reinert, G. The rate of convergence of some asymptotically chi-square distributed statistics by Stein’s method. arXiv:1603:01889, 2016

2016

Closest in time.

Anastasiou, A. and Ley, C. Bounds for the asymptotic normality of the maximum likelihood estimator using the Delta method. ALEA Lat. Am. J. Probab. Math. Stat. 𝟏𝟒 \mathbf{14} (2017), 153–171

2017

Closest in time.

Anastasiou, A. and Reinert, G. Bounds for the normal approximation of the maximum likelihood estimator. Bernoulli 𝟐𝟑 \mathbf{23} (2017), pp. 191–218

2017

Closest in time.