46 citations · 84 across the 11 of their papers we have counts for
9 papers · 1 filter
Wasserstein distance bounds on the normal approximation of empirical autocovariances and cross-covariances under non-stationarity and stationarity
Andreas Anastasiou, Tobias Kley
The autocovariance and cross-covariance functions naturally appear in many time series procedures (e.g., autoregression or prediction). Under assumptions, empirical versions of the…
Wasserstein distance error bounds for the multivariate normal approximation of the maximum likelihood estimator
Andreas Anastasiou, Robert E. Gaunt
We obtain explicit -Wasserstein distance error bounds between the distribution of the multi-parameter MLE and the multivariate normal distribution. Our general bounds are given…
Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT
Andreas Anastasiou, Krishnakumar Balasubramanian, Murat A. Erdogdu
We provide non-asymptotic convergence rates of the Polyak-Ruppert averaged stochastic gradient descent (SGD) to a normal random vector for a class of twice-differentiable test func…
Bounds for the asymptotic distribution of the likelihood ratio
Andreas Anastasiou, Gesine Reinert
In this paper we give an explicit bound on the distance to chisquare for the likelihood ratio statistic when the data are realisations of independent and identically distributed ra…
Bounds for the normal approximation of the maximum likelihood estimator from m-dependent random variables
Andreas Anastasiou
The asymptotic normality of the Maximum Likelihood Estimator (MLE) is a long established result. Explicit bounds for the distributional distance between the distribution of the MLE…
Multivariate normal approximation of the maximum likelihood estimator via the delta method
Andreas Anastasiou, Robert E. Gaunt
We use the delta method and Stein's method to derive, under regularity conditions, explicit upper bounds for the distributional distance between the distribution of the maximum lik…
Assessing the multivariate normal approximation of the maximum likelihood estimator from high-dimensional, heterogeneous data
Andreas Anastasiou
The asymptotic normality of the maximum likelihood estimator (MLE) under regularity conditions is a cornerstone of statistical theory. In this paper, we give explicit upper bounds…
Bounds for the asymptotic normality of the maximum likelihood estimator using the Delta method
Andreas Anastasiou, Christophe Ley
The asymptotic normality of the Maximum Likelihood Estimator (MLE) is a cornerstone of statistical theory. In the present paper, we provide sharp explicit upper bounds on Zolotarev…
Bounds for the normal approximation of the maximum likelihood estimator
Andreas Anastasiou, Gesine Reinert
While the asymptotic normality of the maximum likelihood estimator under regularity conditions is long established, this paper derives explicit bounds for the bounded Wasserstein d…