Least squares data fitting
It is desired to represent, as good as possible, a series of data by means of certain functions with free parameters. "As good as possible" means that these parameters ara chosen so that the residuals, the difference between data and fitting functions, be as small as it is feasible. Our...
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| Format: | Article |
| Language: | English |
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Universidad Autónoma de Baja California
2002-03-01
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| Series: | Ciencias Marinas |
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| Online Access: | https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/204 |
| _version_ | 1827330872903204864 |
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| author | P Ripa |
| author_facet | P Ripa |
| author_sort | P Ripa |
| collection | DOAJ |
| description |
It is desired to represent, as good as possible, a series of data by means of certain functions with free parameters. "As good as possible" means that these parameters ara chosen so that the residuals, the difference between data and fitting functions, be as small as it is feasible. Our objective is not limited to finding the parameters of the best fit, but we also wish to know something about their uncertainties, this is, how well they are determined, given the errors of the original data as well as the imperfection of the fitting. Finally, supposing that we use the parameters of the fit in the calculation of other variables, we also want to have an estimation of the uncertainties of the latter. In order to do that, we imagine basic properties, wich we call "hypothesis", and then proceed from there with mathematical rigor. It is not superfluous to remember that the conclusions at wich we arrive depende on the hyphotheses done throughout the way, including the idea that useful information can be extracted from a least squares fit, of those data by these functions.
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| first_indexed | 2024-03-07T16:24:46Z |
| format | Article |
| id | doaj.art-8b199d7c36224d80907f90c41f306a0e |
| institution | Directory Open Access Journal |
| issn | 0185-3880 2395-9053 |
| language | English |
| last_indexed | 2024-03-07T16:24:46Z |
| publishDate | 2002-03-01 |
| publisher | Universidad Autónoma de Baja California |
| record_format | Article |
| series | Ciencias Marinas |
| spelling | doaj.art-8b199d7c36224d80907f90c41f306a0e2024-03-03T19:27:06ZengUniversidad Autónoma de Baja CaliforniaCiencias Marinas0185-38802395-90532002-03-0128110.7773/cm.v28i1.204Least squares data fittingP Ripa0Centro de Investigación Científica y de Educación Superior de Ensenada It is desired to represent, as good as possible, a series of data by means of certain functions with free parameters. "As good as possible" means that these parameters ara chosen so that the residuals, the difference between data and fitting functions, be as small as it is feasible. Our objective is not limited to finding the parameters of the best fit, but we also wish to know something about their uncertainties, this is, how well they are determined, given the errors of the original data as well as the imperfection of the fitting. Finally, supposing that we use the parameters of the fit in the calculation of other variables, we also want to have an estimation of the uncertainties of the latter. In order to do that, we imagine basic properties, wich we call "hypothesis", and then proceed from there with mathematical rigor. It is not superfluous to remember that the conclusions at wich we arrive depende on the hyphotheses done throughout the way, including the idea that useful information can be extracted from a least squares fit, of those data by these functions. https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/204Least squaresdata fitting |
| spellingShingle | P Ripa Least squares data fitting Ciencias Marinas Least squares data fitting |
| title | Least squares data fitting |
| title_full | Least squares data fitting |
| title_fullStr | Least squares data fitting |
| title_full_unstemmed | Least squares data fitting |
| title_short | Least squares data fitting |
| title_sort | least squares data fitting |
| topic | Least squares data fitting |
| url | https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/204 |
| work_keys_str_mv | AT pripa leastsquaresdatafitting |