mODa 10 – Advances in Model-Oriented Design and Analysis

Proceedings of the 10th International Workshop in Model-Oriented Design and Analysis Held in Łagów Lubuski, Poland, June 10–14, 2013

  • Dariusz Ucinski
  • Anthony C. Atkinson
  • Maciej Patan
Conference proceedings

Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Table of contents

  1. Front Matter
    Pages I-XX
  2. Giacomo Aletti, Caterina May, Chiara Tommasi
    Pages 1-9
  3. Anthony C. Atkinson, Barbara Bogacka
    Pages 11-18
  4. Roelof L. J. Coetzer, Linda M. Haines
    Pages 45-53
  5. Nancy Flournoy, Arkaitz Galbete, José Antonio Moler, Fernando Plo
    Pages 81-89
  6. David Ginsbourger, Nicolas Durrande, Olivier Roustant
    Pages 107-115
  7. Ulrike Graßhoff, Heinz Holling, Rainer Schwabe
    Pages 117-124
  8. Markus Hainy, Werner G. Müller, Henry P. Wynn
    Pages 135-143
  9. Bergrun Tinna Magnusdottir
    Pages 153-161
  10. Viatcheslav B. Melas, Lyudmila A. Krylova, Dariusz Uciński
    Pages 163-170
  11. Ewaryst Rafajłowicz, Wojciech Rafajłowicz
    Pages 219-227
  12. Ewa Skubalska-Rafajłowicz, Ewaryst Rafajłowicz
    Pages 229-236
  13. HaiYing Wang, Andrey Pepelyshev, Nancy Flournoy
    Pages 237-245
  14. Back Matter
    Pages 247-249

About these proceedings


This book collects the proceedings of the 10th Workshop on Model-Oriented Design and Analysis (mODa). A model-oriented view on the design of experiments, which is the unifying theme of all mODa meetings, assumes some knowledge of the form of the data-generating process and naturally leads to the so-called optimum experimental design. Its theory and practice have since become important in many scientific and technological fields, ranging from optimal designs for dynamic models in pharmacological research, to designs for industrial experimentation, to designs for simulation experiments in environmental risk management, to name but a few. The methodology has become even more important in recent years because of the increased speed of scientific developments, the complexity of the systems currently under investigation and the mounting pressure on businesses, industries and scientific researchers to reduce product and process development times. This increased competition requires ever increasing efficiency in experimentation, thus necessitating new statistical designs. This book presents a rich collection of carefully selected contributions ranging from statistical methodology to emerging applications. It primarily aims to provide an overview of recent advances and challenges in the field, especially in the context of new formulations, methods and state-of-the-art algorithms. The topics included in this volume will be of interest to all scientists and engineers and statisticians who conduct experiments.


clinical trials mixed-effects models nonlinear models

Editors and affiliations

  • Dariusz Ucinski
    • 1
  • Anthony C. Atkinson
    • 2
  • Maciej Patan
    • 3
  1. 1.University of Zielona GóraZielona GóraPoland
  2. 2.London School of EconomicsLondonUnited Kingdom
  3. 3.University of Zielona GóraZielona GóraPoland

Bibliographic information