Beschreibung
InhaltsangabeInvited papers.- The history of COMPSTAT and key-steps of statistical computing during the last 30 years.- Hybrid algorithms for construction of D-efficient designs.- Geometry of learning in in multilayer perceptrons.- Visual data mining for quantized spatial data.- Graphs for representing statistics indexed by nucleotide or amino acid sequences.- Matrix visualization and information mining.- st-apps and EMILeA-stat: Interactive visualizations in descriptive statistics.- The case sensitivity function approach to diagnostic and robust computation: A relaxation strategy.- On the bootstrap methodology for functional data.- A novel approach to parametrization and parameter estimation in linear dynamic systems.- Statistical analysis of handwritten Arabic numerals in a Chinese population.- Methods and algorithms for robust filtering.- Using GO for statistical analyses.- Computational challenges in determining an optimal design for an experiment.- Visualization of parametric carcinogenesis models.- Design aspects of a computer simulation study for assessing uncertainty in human lifetime toxicokinetic models.- Simultaneous inference in risk assessment; a Bayesian perspective.- Interactive biplots for visual modelling.- R: The next generation.- Robust multidimensional scaling.- Improved jackknife variance estimates of bilinear model parameters.- Line mosaic plot: Algorithm and implementation.- Graphical displays of Internet traffic data.- Clustering all three modes of three-mode data: Computational possibilities and problems.- Functional data analysis and mixed effect models.- Using weights with a text proximity matrix.- On canonical analysis of vector time series.- Learning statistics by doing or by describing: The role of software.- Embedding methods and robust statistics for dimension reduction.- A general partition cluster algorithm.- Iterative denoising for cross-corpus discovery.- From data to differential equations.- Simple simulations for robust tests of multiple outliers in regression.- The St@tNet project for teaching statistics.- An automatic thresholding approach to gene expression analysis.- Kernel methods for manifold estimation.- Outlier detection and clustering by partial mixture modeling.- InterDatabase and DandD.- Exploratory visual analysis of graphs in GGobi.- PLS regression and PLS path modeling for multiple table analysis.- 1001 graphics.- Fitting Bradley Terry Models using a multiplicative algorithm.- Modelling multiple time series: Achieving the aims.- Total least squares and errors-in-variables modeling: Bridging the gap between statistics, computational mathematics and engineering.- Author Index.- COMPSTAT 2004 Section Index.
