ENBIS-15 in Prague6 – 10 September 2015; Prague, Czech Republic Abstract submission: 1 February – 3 July 2015
The following abstracts have been accepted for this event:
Alternative Statistical Analysis of Interlaboratory Comparison Measurement Results
Authors: Rossella Berni (Department of Statistics, Computer Science and Applications "G.Parenti", University of Florence), Carlo Carobbi (Department of Information Engineering, University of Florence)
Primary area of focus / application: Other: ENBIS session at IMEKO
Secondary area of focus / application: Metrology & measurement systems analysis
Keywords: Proficiency test, Interlaboratory comparisons, Key-comparisons, Error measurement model
Submitted at 29-Apr-2015 20:42 by Rossella Berni
 Statistical Methods for Use in Proficiency Testing by Interlaboratory Comparison, ISO 13528: 2005.
Predicting the Evolution of Worldwide Financial Markets with the Popularity of Key Words in the Google Browser through a Compositional Approach
Authors: Robert Ortells (Universitat Politècnica de Catalunya), Juan Jose Egozcue (Universitat Politècnica de Catalunya), Maribel Ortego (Universitat Politècnica de Catalunya), Alvar Garola (Universitat Politècnica de Catalunya)
Primary area of focus / application: Economics
Secondary area of focus / application: Other: Compositional Analysis of Data
Keywords: Compositional data, Worldwide financial markets, Stock market, Sovereign debt yield, Commodities, Multiple linear regression, Google
Submitted at 29-Apr-2015 22:17 by Robert Ortells
The key concept of the analysis is that a conventional multiple regression model cannot be proposed straight away, since both the explanatory and response variables have a specific nature that must be taken into consideration. With reference to the response variable (worldwide financial indexes involving equities, sovereign debt yields and commodities), we can see that the important information is not in the actual values for the indexes but in the relationships between them. Indeed, performance of financial indexes has to be evaluated through comparing them with respect to other indexes. For example, a positive evolution for a stock market index needs to be analyzed by looking at other stock market indexes (apart from other relevant financial indexes), otherwise erroneous conclusions might be drawn. Therefore, since the relevant information is not in the numerical values but in the relationships with the rest, a compositional approach seems appropriate. Regarding the information of the popularity of the words in the internet browser, the same reasoning seems to be adequate. For instance, in case the word bankruptcy increases in popularity for a certain week and the other words present a similar increase, the information we might infer from such search patterns is the same. However, in case the searches increase for such word and remain quite the same for the rest, this may be relevant. Therefore, the information on the popularity of the different terms presents a compositional nature as well, so it must be treated accordingly before performing any regression.
For the reasons we have just set, a compositional approach seems necessary in order to address the problem successfully, since both the explanatory and the response variables present a compositional nature. Once the data has been appropriately treated, an exploratory analysis has been performed on both data sets (popularity of 200 different words and numerical values of 19 financial indexes along the period 2004-2014). After that, a multiple linear regression model between them has been proposed. Finally, the results have been compared to previous research in the field.
How Well Do We Need to Measure Our Drilling Mud?
Authors: Winfried Theis (Shell Global Solutions International B.V.)
Primary area of focus / application: Design and analysis of experiments
Secondary area of focus / application: Quality
Keywords: Measurement uncertainty, Design of Experiments, Computer experiments, Quality by design
Submitted at 30-Apr-2015 03:06 by Winfried Theis
Introduction to Compositional Data Analysis with Applications to Customer Survey Analysis
Authors: Marina Vives-Mestres (Universitat de Girona), Josep-Antoni Martín-Fernández (Universitat de Girona), Ron Kenett (KPA Group)
Primary area of focus / application: Other: Compositional Analysis of Data
Keywords: Customer survey analysis, Compositional data analysis, Logratio coordinates, Simplex
Submitted at 30-Apr-2015 07:28 by Marina Vives-Mestres
We finish this introductory session with an example of applications in the field of customer survey analysis. Specifically, we analyse the annual customer satisfaction survey of the ABC Company presented and analysed in detail in the book edited by Kenett and Salini (2011). The questionnaire consists of an assessment of overall satisfaction evaluated on a five-point anchored scale, so that it can be analysed from a CoDa perspective, and almost 50 statements with two types of scores: an evaluation score and a measure of item importance. Other questions such as repurchasing intentions and descriptive variables for each customer are used in analysing the ABC dataset.
We show how CoDa methods can contribute to provide a map of customer’s opinion, improve decision making, identify improvement areas or weak points, set service level targets and help improve the questionnaire itself. We also compare the findings to several statistical models presented in Kenett and Salini (2011) such as PLS, hierarchical models, fuzzy sets, log-linear models and control charts. Graphical tools to communicate CoDa results are also proposed. The general idea is that one can increase the information quality of a customer survey analysis by combining more than one technique.
Following this introductory talk, a special CoDa session will include two additional application examples as well as a practical and interactive CoDa hands-on session. The audience is highly encouraged to attend the special CoDa session and enjoy the hands-on experience that will be delivered.
Kenett, RS., Salini, S. (2011). Modern Analysis of Customer Satisfaction Surveys: with applications using R. Chichester: UK. JohnWiley and Sons.
On- and Offline Detection of Structural Breaks in Thermal Spraying Processes
Authors: Nikolaus Rudak (Dortmund University of Applied Sciences and Arts), Matthias Borowski (Institute of Biostatistics and Clinical Research), Birger Hussong (Faculty of Mechanical Engineering), Dominik Wied (TU Dortmund University), Sonja Kuhnt (Dortmund University of Applied Sciences and Arts), Wolfgang Tillmann (Faculty of Mechanical Engineering)
Primary area of focus / application: Process
Keywords: Jumps, Trends, Variance changes, Thermal spraying process
Submitted at 30-Apr-2015 09:06 by Nikolaus Rudak
We use a robust online filtering procedure for detecting jumps in the mean and modify this method slightly in order to detect ongoing trends. Furthermore, we utilize a fluctuation test for constant variances. We investigate the mentioned methods by simulations and apply them to data coming from experiments where the engineer provokes several technical malfunctions during the thermal spraying process (Borowski et al. (2014)).
1. Rudak, N., Kuhnt, S., Hussong, B. and Tillmann, W. (2012), "On
different strategies for the prediction of coating properties in a HVOF process", SFB 823 Discussion Paper 29/12, TU Dortmund University.
2. Borowski, M., Rudak, N., Hussong, B., Wied, D., Kuhnt, S., Tillmann, W. (2014), "On- and offline detection of structural breaks in thermal spraying processes", Journal of Applied Statistics, 41 (5), 1073-1090.
A Discussion on the Concept and Objectives of Blocking and Robustness in Industrial Experiments
Authors: Xavier Tort-Martorell (UPC Universitat Politécnica de Catalunya, Barcelona Tech), Lluís Marco-Almagro (UPC Universitat Politécnica de Catalunya), Pere Grima (UPC Universitat Politécnica de Catalunya)
Primary area of focus / application: Design and analysis of experiments
Keywords: Industrial experiments, Factorial designs, Blocking, Robustness, Taguchi
Submitted at 30-Apr-2015 09:48 by Xavier Tort-Martorell
Accepted (view paper)
In this presentation we will argue that in many real world situations, and in fact in all the examples used in the above mentioned books to illustrate blocking, it is a better conceptual and practical option to design an experiment with the aim of achieving robustness than to block the design.
Attention will be devoted to the rather different philosophy/intuition underlying the two approaches. In the case of blocking it is assumed that the blocking factors do not interact with the other experimental factors, while in the case of robustness the hope is that the noise factors interact with the control factors.