1. Cross-covariance isolate detect: a new change-point method for estimating dynamic functional connectivity. Anastasiou, A., Cribben, I. & Fryzlewicz, P. (2021+). In submission.

2. Wasserstein distance error bounds for the multivariate normal approximation of the maximum likelihood estimator. Anastasiou, A. & Gaunt, R. E. (2021+) arXiv:2005.05208 [math.ST]. In submission.

3. Modeling of Covid-19 Pandemic in Cyprus. Agapiou, S., Anastasiou, A., Baxevani, A., Christofides, T., Constantinou, E., Hadjigeorgiou, G., Nicolaides, C., Nikolopoulos, G. & Fokianos, K. (2021+) arXiv:2010.01927 [stat.AP]. In submission.  

4. Detecting multiple generalized change-points by isolating single ones. Anastasiou, A. & Fryzlewicz, P. (2021+). With supplement. arXiv:1901.10852 [stat.ME]. In submission.

5. Bounds for the asymptotic distribution of the likelihood ratio. Anastasiou, A. & Reinert, G. (2020). Annals of Applied Probability, 30, No. 2, 608-643.

6. Multivariate normal approximation of the maximum likelihood estimator via the delta method. Anastasiou, A. & Gaunt, R. E. (2020). Brazilian Journal of Probability and Statistics, 34, 136-149.

7. 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.

8. 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.

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

10. 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.

11. 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]

2. breakfast: Computationally Efficient Multiple Change-Point Detection and Estimation with a Broad Range of Methods. R package. [CRAN]

3. ccid: a change-point detection method for estimating dynamic functional connectivity. R package. [CRAN]