As estimators of location parameters, univariate trimmed means are well-known for their robustness and efficiency. They can serve as robust alternatives to the sample mean while possessing high efficiencies at normal as well as heavy tailed models. This paper introduces multi-dimensional trimmed means based on projection depth induced regions. Robustness of these depth trimmed means is investig...

We propose the quasi-maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.

In this paper, we consider a number of technical problems associated with identification of linear systems using quantized and intermittent information. More specifically, we study asymptotic properties for identification of such systems, including strong consistency, asymptotic normality and asymptotic efficiency, and determine their relationship with quantization errors and the packet losses....

A method is proposed for estimating the potential function of a non-parametric estimator for stationary and isotropic pairwise interaction point process. The relation between a pair potential and the corresponding Papangelou conditional intensity is considered. Consistency and strong consistency of non-parametric estimate are proved in case of finite-range interaction potential.

In this paper, we prove the strong uniform consistency and asymptotic normality of the kernel density estimator proposed by Jones [12] for length-biased data.The approach is based on the invariance principle for the empirical processes proved by Horváth [10]. All simulations are drawn for different cases to demonstrate both, consistency and asymptotic normality and the method is illustrated by ...

We introduce an abstract model of exact learning via queries that can be instantiated to all the query learning models currently in use, while being closer to them than previous uniicatory attempts. We present a characterization of those Boolean function classes learnable in this abstract model, in terms of a new combinatorial notion that we introduce, the abstract identiication dimension. Then...

We study the quantum analogue of primary fields and their descendants on fuzzy AdS2, proposed in hep-th/0004072. Three-point vertices are calculated and shown to exhibit the conventional 1/N expansion as well as nonperturtive effects in large N , thus providing a strong consistency check of the fuzzy AdS2 model. A few new physical motivations for this model are also presented.

The aim of this article is to simplify Pfanzagl’s proof of consistency for asymptotic maximum likelihood estimators, and to extend it to more general asymptotic M -estimators. The method relies on the existence of a sort of contraction of the parameter space which admits the true parameter as a fixed point. The proofs are short and elementary.

We study the problem of inferring policy intent to identify misconfigurations in access control implementations. This is in contrast to traditional role-mining techniques, which focus on creating better abstractions for access control management. We show how raw metadata can be summarized effectively, by grouping together users with similar permissions over shared resources. Using these summary...

The regenerative method for estimating steady-state parameters is one of the basic methods in the simulation literature. This method depends on central limit theorems for regenerative processes and weakly consistent estimates for the variance constants arising in the central limit theorem. A weak sufficient (and probably necessary) condition for both the central limit theorems and consistent es...