Titlebook: Exploratory Data Analysis in Empirical Research; Proceedings of the 2 Manfred Schwaiger,Otto Opitz Conference proceedings 2003 Springer-Ver

Diastole

Chronic

Sliced Inverse Regression for High-dimensional Time Seriesany parameters because of interactions at various time-lags. We use a dynamic version of Sliced InverseRegression (SIR; (.)) as an exploratory tool for analyzing multivariate time series. Analyzing each variable individually, wesearch for those directions, i.e, linear combinations of past and presen

adroit

Symbolic Clustering of Constrained Probabilistic Datalustering method. In another paper Brito (1998) has addressed the problem of clustering probabilistic data. The aim of this paper is to bring together the two issues, that is, to take into account dependence rules on probabilistic data. This is accomplished by introducing new generality measures wit

Forsake

Congregate

On the Roles of Galois Connections in Classificationuses, we select some topics related with modelization and aggregat ion of dissimilarities and conceptual classification. We partially revisit them in a common frame provided by a recent study about Galois connections between closure spaces.

討好美人

Mining Sets of Time Series: Description of Time Pointsing time series. This paper addresses the problem how to choose the attributes describing the time points with respect to certain matching problem. Furthemore, this paper introduce an algorithm, computing the domain error of a classifier of the model, which can be used as an evaluation function of t

使迷惑

Spatial Smoothing with Robust Priors in Functional MRIvated by a particular stimulus requires elaborate models and efficient algorithms. Based on regressionmodels of the observedMR signals on the presented stimulus, pixelwise and spatial techniques have been applied. Besides describing the stimulus dependence of the MR signal, the latter also include s

兇兆

借喻

obscurity