Title :
A geometric approach to statistical estimation
Author_Institution :
Inst. of Inf. Theory & Autom., Acad. of Sci., Prague, Czech Republic
Abstract :
The role of Kerridge inaccuracy, Shannon entropy and Kullback-Leibler distance in statistical estimation is shown for both discrete and continuous observations. The cases of data independence and regression-type dependence are considered in parallel. Pythagorean-like relations valid for probability distributions are presented and their importance for estimation under compressed data is indicated
Keywords :
differential geometry; entropy; information theory; maximum likelihood estimation; parameter estimation; probability; statistical analysis; Kerridge inaccuracy; Kullback-Leibler distance; Pythagorean-like relations; Shannon entropy; compressed data; continuous observations; discrete observations; probability distributions; regression-type dependence; statistical estimation; Automation; Density measurement; Entropy; Information theory; Particle measurements; Probability distribution; Robustness; Statistics; System identification; Uncertainty;
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-2685-7
DOI :
10.1109/CDC.1995.480237
