ArticleOriginal scientific text

Title

Statistical analysis of diabetes mellitus

Authors 1

Affiliations

  1. Universität Kassel, Fachbereich 17 Mathematik/Informatik, Heinrich-Plett-Straße 40, D-34132 Kasse

Abstract

This paper deals with an application of regression analysis to the regulation of the blood-sugar under diabetes mellitus. Section 2 gives a description of Gram-Schmidt orthogonalization, while Section 3 discusses the difference between Gauss-Markov estimation and Least Squares Estimation. Section 4 is devoted to the statistical analysis of the blood-sugar during the night. The response change of blood-sugar is explained by three variables: time, food and physical activity ("Bewegung"). At the beginning of the section it is shown that the proposed method was very successful in 2007.

Keywords

Gram-Schmidt orthogonalization, regression model, Gauss-Markov theorem, least squares, diabetes mellitus, glucosis, antidiabetica

Bibliography

  1. H. Drygas, The coordinate-free approach to Gauss-Markov estimation, Lecture notes in Operations Research and Mathematical Systems, Springer-Verlag Berlin-Heidelberg-New York 1970.
  2. H. Drygas, QR-decomposition from the statistical point of view, Recent Advances in Linear Models and Related Areas, Essays in Honour of Helge Toutenburg, Shalabh and Heumann (Eds) p. 293-311, Physica-Verlag, Springer, Heidelberg 2008.
  3. L. Schmetterer, Einführung in die Mathematische Statistik, 2. Auflage, Springer-Verlag Wien-New York 1966.
  4. S. Debasis and S.R. Jammalamadaka, Linear Models, An integrated approach, World Scientific, New Jersey-London-Singapore-Hong Kong 2003.
Pages:
69-90
Main language of publication
English
Received
2009-05-04
Accepted
2009-08-22
Published
2009
Exact and natural sciences