Scan Statistics

Methods and Applications

  • Joseph Glaz
  • Vladimir Pozdnyakov
  • Sylvan Wallenstein

Part of the Statistics for Industry and Technology book series (SIT)

Table of contents

  1. Front Matter
    Pages i-xxviii
  2. Sylvan Wallenstein
    Pages 1-25
  3. Narayanaswamy Balakrishnan, Hon Keung Tony Ng
    Pages 27-54
  4. Michael V. Boutsikas, Markos V. Koutras, Fotios S. Milienos
    Pages 55-85
  5. Hock Peng Chan, I-Ping Tu, NancyRuonan Zhang
    Pages 87-108
  6. Marcelo Azevedo Costa, Martin Kulldorff
    Pages 129-152
  7. Luiz Duczmal, Anderson Ribeiro Duarte, Ricardo Tavares
    Pages 153-177
  8. George Haiman, Cristian Preda
    Pages 179-193
  9. Josephine Hoh, Jurg Ott
    Pages 195-202
  10. Daniel B. Neill, Gregory F. Cooper, Kaustav Das, Xia Jiang, Jeff Schneider
    Pages 221-249
  11. Ganapati P. Patil, Sharadchandra W. Joshi, Wayne L. Myers, Rajesh E. Koli
    Pages 251-270
  12. Marco Perone-Pacifico, Isabella Verdinelli
    Pages 271-287
  13. Vladimir Pozdnyakov, J. Michael Steele
    Pages 289-317
  14. Sophie Schbath, Stéphane Robin
    Pages 319-350
  15. Valeri T. Stefanov
    Pages 351-367
  16. Toshiro Tango
    Pages 369-391
  17. Back Matter
    Pages 393-394

About this book


Scan statistics is currently one of the most active and important areas of research in applied probability and statistics, having applications to a wide variety of fields: archaeology, astronomy, bioinformatics, biosurveillance, molecular biology, genetics, computer science, electrical engineering, geography, material sciences, physics, reconnaissance, reliability and quality control, telecommunication, and epidemiology.

Filling a gap in the literature, this self-contained volume brings together a collection of selected chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.

Key features:

* Chapters are written by leading experts in the field.

* Features many current results and highlights new directions for future research.

* Includes challenging theoretical methodological research problems.

* Presentation is accessible to statisticians as well as to scientists from other disciplines where scan statistics are employed.

* Real-world applications to areas such as bioinformatics and biosurveillance are emphasized.

* Contains extensive references to research articles, books, and relevant computer software.


Scan Statistics is an excellent reference for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science, medicine, geography, quality control, communications, and epidemiology. The work may also be used as a textbook for a graduate-level seminar on scan statistics.


Excel Martingale Radiologieinformationssystem algorithms bioinformatics calculus clustering martingale methods protein and DNA sequences quality control scan statistics scan statistics applications scan statistics applications, health sciences

Editors and affiliations

  • Joseph Glaz
    • 1
  • Vladimir Pozdnyakov
    • 2
  • Sylvan Wallenstein
    • 3
  1. 1.Dept. StatisticsUniversity of ConnecticutStorrsU.S.A.
  2. 2.Dept. StatisticsUniversity of ConnecticutStorrsU.S.A.
  3. 3.Center for Biomathematical SciencesMount Sinai School of MedicineNew YorkU.S.A.

Bibliographic information