Geodesic
Statistical analysis of diabetes mellitus
Discussiones Mathematicae. Probability and Statistics, Tome 29 (2009) no. 1, pp. 69-90

Voir la notice de l'article provenant de la source Library of Science

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 
Drygas, Hilmar. Statistical analysis of diabetes mellitus. Discussiones Mathematicae. Probability and Statistics, Tome 29 (2009) no. 1, pp. 69-90. http://geodesic.mathdoc.fr/item/DMPS_2009_29_1_a4/
@article{DMPS_2009_29_1_a4,
     author = {Drygas, Hilmar},
     title = {Statistical analysis of diabetes mellitus},
     journal = {Discussiones Mathematicae. Probability and Statistics},
     pages = {69--90},
     year = {2009},
     volume = {29},
     number = {1},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/DMPS_2009_29_1_a4/}
}
TY  - JOUR
AU  - Drygas, Hilmar
TI  - Statistical analysis of diabetes mellitus
JO  - Discussiones Mathematicae. Probability and Statistics
PY  - 2009
SP  - 69
EP  - 90
VL  - 29
IS  - 1
UR  - http://geodesic.mathdoc.fr/item/DMPS_2009_29_1_a4/
LA  - en
ID  - DMPS_2009_29_1_a4
ER  - 
%0 Journal Article
%A Drygas, Hilmar
%T Statistical analysis of diabetes mellitus
%J Discussiones Mathematicae. Probability and Statistics
%D 2009
%P 69-90
%V 29
%N 1
%U http://geodesic.mathdoc.fr/item/DMPS_2009_29_1_a4/
%G en
%F DMPS_2009_29_1_a4

[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.