1. Bounds for the asymptotic distribution of the likelihood ratio. Anastasiou, A. & Reinert, G. (2019+). arXiv:1806.03666 [math.ST]. To appear in Annals of Applied Probability.

2. Multivariate normal approximation of the maximum likelihood estimator via the delta method. Anastasiou, A. & Gaunt, R. (2019+). arXiv:1609.03970 [math.ST]. To appear in the Brazilian journal of Probability and Statistics.

3. Detecting multiple generalized change-points by isolating single ones. Anastasiou, A. & Fryzlewicz, P. (2019+). With supplement. arXiv:1901.10852 [stat.ME]. In submission.

4. Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT. Anastasiou, A, & Balasubramanian, K. & Erdogdu, M. (2019). Proceedings of the Conference on Learning Theory (COLT) 2019.

5. Assessing the multivariate normal approximation of the maximum likelihood estimator from high-dimensional, heterogeneous data. Anastasiou, A. (2018). Electronic Journal of Statistics, 12, No. 2, 3794-3828.

6. Bounds for the normal approximation of the maximum likelihood estimator. Anastasiou, A. & Reinert, G. (2017). Bernoulli 23, 191-218. 

7. Bounds for the asymptotic normality of the maximum likelihood estimator using the Delta method. Anastasiou, A. & Ley, C. (2017).  ALEA, Lat. Am. J. Probab. Math. Stat. 14, 153-171.

8. Bounds for the normal approximation of the maximum likelihood estimator from m-dependent random variables. Anastasiou, A. (2017). Statistics & Probability Letters 129, 171-181.

- Claude Bernard -

“The joy of discovery is certainly the liveliest that the mind of man can ever feel”

PUBLICATIONS AND PREPRINTS

SOFTWARE

1. IDetect: Isolate-Detect Methodology for Multiple Change-Point Detection. R package. [CRAN]