This paper describes some techniques for proving asymptotic normality of statistics defined by maximization of random criterion function. The techniques are based on a combination of recent results from the theory of empirical processes and a method of Huber for the study of maximum likelihood...

This paper studies a class of exponential family models whose canonical parameters are specified as linear functionals of an unknown infinite-dimensional slope function. The optimal minimax rates of convergence for slope function estimation are established. The estimators that achieve the...

The process and rate of internationalisation of Czech SMEs has recently been affected through the country's accession to the EU. It seems appropriate, therefore, to re-assess the internationalisation processes of Czech SMEs and potential barriers to their entering foreign markets. The aims of...

The creation of a new joint venture, involving Scottish and Thai partner organisations, is analysed with regard to the initial setting up of collaborative operations and a pre-implementation programme of knowledge transfer in the context of economic uncertainty. The study concludes that, in...

The introduction of the Closer Economic Partnership Arrangement (CEPA) at the beginning of 2004 and, more recently, CEPA-2 has provided a framework for increased business development in the Pearl River Delta area of China and the Special Administrative Regions of Macau and Hong Kong. In...

This paper contains a review of the current debate concerning SME internationalisation and sets out a research agenda for investigating SME internationalisation in transformation economies. Current developments and various theoretical approaches in explaining the dynamics of SME...

A general central limit theorem is proved for estimators defined by minimization of the length of a vector-valued, random criterion function. No smoothness assumptions are imposed on the criterion function in order that the results might apply to a broad class of simulation estimators. Complete...

The paper uses empirical process techniques to study the asymptotics of the least-squares estimator (LSE) for the fitting of a nonlinear regression function. By combining and extending ideas of Wu and Van de Geer, it establishes new consistency and central limit theorems that hold under only...

This paper shows how the modern machinery for generating abstract empirical central limit theorems can be applied to arrays of dependent variables. It develops a bracketing approximation based on a moment inequality for sums of strong mixing arrays, in an effort to illustrate the sorts of...

The LAD estimator of the vector parameter in a linear regression is defined by minimizing the sum of the absolute values of the residuals. This paper provides a direct proof of asymptotic normality for the LAD estimator. The main theorem assumes deterministic carriers. The extension to random...