ENBIS: European Network for Business and Industrial Statistics
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ENBIS12 in Ljubljana
9 – 13 September 2012 Abstract submission: 15 January – 10 May 2012The following abstracts have been accepted for this event:

Threestage Industrial Stripplot Experiments
Authors: Heide Arnouts (University of Antwerp), Peter Goos (University of Antwerp)
Primary area of focus / application: Design and analysis of experiments
Keywords: stripplot design, threestage processes, splitsplitplot design, Doptimality
Submitted at 6Apr2012 14:55 by Heidi Arnouts
Accepted

PM10 Forecasting Using Mixture Linear Regression Models
Authors: JeanMichel Poggi (University of Paris Descartes), Bruno Portier (INSA Rouen), Michel Misiti (University of Orsay), Yves Misiti (University of Orsay)
Primary area of focus / application: Modelling
Keywords: particulate matter, forecasting, clusterwise linear models, air quality
Submitted at 7Apr2012 17:27 by JeanMichel Poggi
Accepted
We accurately forecast the daily mean concentration by fitting a function of meteorological predictors and the average concentration measured on the previous day. The values of observed meteorological variables are used for fitting the models but the corresponding predictions are considered for the test data, leading to realistic evaluations of forecasting performances which are calculated through a leaveoneout scheme on the four years.
We discuss in this talk several methodological issues including various estimation schemes, the introduction of the deterministic predictions of meteorological or numerical models and the way to handle the forecasting at various horizons from some hours to one day ahead. 
People Make Mistakes  Unavoidable....
Authors: Johan Batsleer (Amelior)
Primary area of focus / application: Quality
Keywords: human error, quality management, mistakes, brain
But how can we match that with the idea that paople will always make mistakes.
Especially when there is routine, the chance of making mistakes will be present and could be something like 3 on 1000.
Today we can look in the human brain and we can try to understand the mechanisme that creates 'human error'. 
Outlier Detection for Business Indicators of Healthcare Quality  A Comparison of Four Approaches to Overdispersed Proportions
Authors: Gaj Vidmar (University of Ljubljana, Faculty of Economics), Rok Blagus (University of Ljubljana, Faculty of Economics)
Primary area of focus / application: Process
Keywords: healthcare quality, performance measures, outliers, control charts, crosssectional data, overdispersion
Submitted at 8Apr2012 22:35 by Gaj Vidmar
Accepted

Fitting Data using Bspline Functions and GA and PSO Bioinspired Methods
Authors: Angel Cobo Ortega (University of Cantabria), Alberto Luceño Vázquez (University of Cantabria), Jaime PuigPey Echebeste (University of Cantabria)
Primary area of focus / application: Mining
Keywords: Bioinspired methods, Genetic Algorithms, Particle Swarm Optimization, Regression, CAD
The p parameter vector in f(x;p) contains the coefficients of a linear combination of Bspline basis functions, the vector of nodes, and the degree of the polynomials in the Bspline base. Whereas f(x;p) is linear with respect to the first group of parameters, the coefficients, it is nonlinear with respect the remaining parameters.
This nonlinearity and the possibly large number of parameters, make the fitting task considerably more difficult than in a linear case. We compare two bioinspired procedures based in Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The fitting process evolves on populations of node vectors, so that the linear coefficients are fitted conditioned to the selected values of the nonlinear parameters, until the quadratic error is minimized.
We examine some examples of data points, showing the performance of both GA and PSO techniques. Twenty runs are performed for each example, fitting a Bspline polynomial with given degree and number of knots in the definition interval. Fitting quality measures are reported to aid comparing GA versus PSO. 
Balancing Interpretation and Prediction Accuracy in Classification and Regression using Local Correlation Information
Authors: Marco S. Reis (University of Coimbra)
Primary area of focus / application: Process
Keywords: partial correlation, clustering, classification, regression, Generalized Topological Overlap Measure, linear discriminant analysis, ordinary/partial least squares
Submitted at 9Apr2012 17:08 by Marco P. Seabra dos Reis
Accepted