Published March 2004
| Version v1
Report
The least squares method formulation with account of systematic errors
Description
Use of the Least Squares Method for simultaneous processing of huge data sets is essentially complicated by two mathematic problems - one arises if regression function is not linear in parameters and second is connected with inversion of 'poorly conditioned' covariance matrix of experimental errors in the case when they are correlated. The first problem can be successfully circumvented by the method of discrete optimization of rational approximants and the way to circumvent the second is described in this article
Additional details
Publishing Information
- Imprint Title
- Summary report of the second research co-ordination meeting on improvement of the standard cross sections for light elements
- Imprint Pagination
- 370 p.
- Journal Page Range
- p. 359-361
- Report number
- INDC(NDS)--453
Conference
- Title
- 2. research co-ordination meeting on improvement of the standard cross sections for light elements
- Dates
- 13-17 Oct 2003
- Place
- Gaithersburg, MD (United States)
INIS
- Country of Publication
- International Atomic Energy Agency (IAEA)
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 35095171
- Subject category
- S99: GENERAL AND MISCELLANEOUS;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- ERRORS; FUNCTIONS; LEAST SQUARE FIT; NUCLEAR DATA COLLECTIONS; OPTIMIZATION
- Descriptors DEC
- MATHEMATICAL SOLUTIONS; MAXIMUM-LIKELIHOOD FIT; NUMERICAL SOLUTION
Optional Information
- Notes
- 2 refs