Abstract
The authors discuss the least-squares procedure for averaging any number of correlated data. In fact, they consider the procedure in its general formulation which serves to determine m parameters by n correlated experimental data on different functions of the parameters. If m>n, the same formulation applies to the adjustment of a given library of m correlated parameters by a set of n relevant correlated data which may even be correlated to the given parameters. There are, however, certain restrictions on the application of the least-squares procedure. Combining averages over two partially overlapping sets of data, for instance, yields a result which is not equal to the average over the union of the two sets. The authors offer a general comment on the applicability of the least-squares method.
| Original language | English |
|---|---|
| Title of host publication | International Symposium on Nuclear Data Evaluation Methodology |
| Subtitle of host publication | Brookhaven National Laboratory, Upton, NY, USA, 12-16 October 1992 |
| Editors | Charles L. Dunford |
| Place of Publication | Singapore |
| Publisher | World Scientific Publishing Co. Pte Ltd |
| Pages | 231 - 6 |
| Number of pages | 6 |
| ISBN (Print) | 981-02-1285-2 |
| State | Published - 1993 |
Bibliographical note
correlated data;least-squares;averaging;Keywords
- data analysis
- least squares approximations
- radiation detection and measurement