Least square fitting with one explicit parameter less

作者：Berg Bernd A^*

来源：Computer Physics Communications, 2016, 200: 254-258.

DOI：10.1016/j.cpc.2015.09.021

• Fitting
• Curve fitting
• Least square fitting

It is shown that whenever the multiplicative normalization of a fitting function is not known, least square fitting by X-2 minimization can be performed with one parameter less than usual by converting the normalization parameter into a function of the remaining parameters and the data.
Program summary
Program title: FITM1 Catalogue identifier: AEYG_v1_0
Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEYG_v1_0.html
Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland
Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html
No. of lines in distributed program, including test data, etc.: 354261
No. of bytes in distributed program, including test data, etc.: 2627533
Distribution format: tar.gz
Programming language: Fortran 77 with standard extensions (tested with g95 on a Mac).
Computer: Any which supports a Fortran 77 compatible compiler.
Operating system: Any with a Fortran 77 compatible compiler.
RAM: 1 Mbyte
Classification: 4.9.
Nature of problem: Least square minimization when one of the free parameters is the multiplicative normalization of the fitting function.
Solution method: Conversion of the normalization constant into a function of the other parameters and the data, resulting into one explicit fitting parameter less.

• 出版日期2016-3