Statistical computing provides the link between statistical theory and applied statistics. As at previous COMPSTAT volumes, the content of the book covers all aspects of this link, from the development and implementation of new statistical ideas to user experiences and software evaluation. The proceedings should appeal to anyone working in statistics and using computers, whether in universities, industrial companies, government agencies, research institutes or as software developers.
Statistical computing provides the link between statistical theory and applied statistics. As at previous COMPSTAT volumes, the content of the book covers all aspects of this link, from the development and implementation of new statistical ideas to user experiences and software evaluation. The proceedings should appeal to anyone working in statistics and using computers, whether in universities, industrial companies, government agencies, research institutes or as software developers. Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Jaromir Antoch, Charles University, Prague, Czech Republic
Inhaltsangabe
Invited 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 fordimension 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.
Invited 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 fordimension 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.
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