A Potential Outcome Approach to Dynamic Programme Evaluation: Nonparametric Identification

A Nonparametric Statistical Approach to Clustering via Mode Identification

In this paper, we develop a mode-based clustering approach applying new optimization techniques to a nonparametric density estimator. A cluster is formed by those sample points that ascend to the same local maximum (mode) of the density function. The path from a point to its associated mode is efficiently solved by an EM-style algorithm, namely, the Modal EM (MEM). This clustering method shares...

A novel approach to outcome evaluation.

Identification, estimation and control of uncertain dynamic systems: a nonparametric approach

This paper is devoted to a short presentation of the use we did of nonparametric estimation theory for the estimation, filtering and control of uncertain dynamic systems. The fundamental advantage of this approach is its low dependence from any a priori modeling assumptions about uncertain dynamic components. It appears to be of great interest for the control of general discrete-time processes,...

A Dynamic Approach to Deductive Query Evaluation

In this paper, a dynamic approach to deductive query evaluation is presented which combines the e ects of di erent SIP strategies used for the magic set rewriting technique. Given a query execution plan obtained by a single magic set transformation, this plan is normally not reoptimized, and the actual number of facts generated during query processing cannot be considered. But applying the magi...

Parametric Versus Nonparametric Approach to Wiener Systems Identification

The problem of nonlinear dynamic systems modelling by means of block-oriented models has been strongly elaborated for the last four decades, due to vast variety of applications. The concept of block-oriented models assumes that the real plant, as a whole, can be treated as a system of interconnected blocks, static nonlinearities (N) and linear dynamics (L), where the interaction signals cannot ...