Data-Oblivious Stream Productivity

We are concerned with demonstrating productivity of specifications of infinite streams of data, based on orthogonal rewrite rules. In general, this property is undecidable, but for restricted formats computable sufficient conditions can be obtained. The usual analysis disregards the identity of data, thus leading to approaches that we call data-oblivious. We present a method that is provably optimal among all such data-oblivious approaches. This means that in order to improve on the algorithm in this paper one has to proceed in a data-aware fashion

Contributions to Mokken's nonparametric item response theory

In this study, the item response models proposed by Mokken (1971) are discussed, and further developed. In these item response models the relation between observable response behavior on an item and latent characteristics of persons and items is described by means of an item characteristic function. Since these functions are not defined parametrically in Mokken's approach, the item response models are called nonparametric. The models proposed by Mokken can be used to scale persons and items on a single dimension. This dimension represents the quantitative measurement scale of a psychological or some other attribute. By measuring persons by means of tests or questionnaires which comply with an item response model, assertions about behavior are psychometrically well founded. ... Zie: Summary