We consider the estimation of error distributions in least squares identiication of distributed parameter systems. Asymptotic properties of approximate error sequences are developed. In particular, we examine consistency and asymptotic normality of empirical estimates of the error distribution. The consistency obtained is analogous to the Glivenko-Cantelli theorem. For asymptotic normality, we ...

We investigate the asymptotic behavior of two types of Tukey depth-based multivariate trimmed means. Sufficient conditions for asymptotic normality of these location estimators are given. Two approaches to trimming are distinguished and central limit theorems are derived for each one. Asymptotic normality is proved using Hadamard differentiability of the location functionals. In the one-dimensi...

This paper establishes a necessary and sufficient condition for the asymptotic normality of the nonparametric estimator of sample coverage proposed by Good [Biometrica 40 (1953) 237–264]. This new necessary and sufficient condition extends the validity of the asymptotic normality beyond the previously proven cases.

We study maximal clades in random phylogenetic trees with the Yule–Harding model or, equivalently, in binary search trees. We use probabilistic methods to reprove and extend earlier results on moment asymptotics and asymptotic normality. In particular, we give an explanation of the curious phenomenon observed by Drmota, Fuchs and Lee (2014) that asymptotic normality holds, but one should normal...