Publication details
OEFPIL: New Method and Software Tool for Fitting Nonlinear Functions to Correlated Data With Errors in Variables
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 14th International Conference on Measurement, MEASUREMENT 2023 |
| MU Faculty or unit | |
| Citation | |
| web | https://doi.org/10.23919/MEASUREMENT59122.2023.10164444 |
| Doi | https://doi.org/10.23919/MEASUREMENT59122.2023.10164444 |
| Keywords | Function Fitting; Nonlinear Regression; Errors in Variables; Correlated Data |
| Description | We present a new method, called OEFPIL, as well as its software implementation for nonlinear function fitting to data with errors in variables where correlation, both within variables and among variables, might be present. In principle, OEFPIL can be employed for fitting both explicit and implicit functions of any number of variables. Importantly, apart from the parameter estimates, OEFPIL also yields their covariance matrix, required for further analyses. Multiple comparisons with existing methods on various types of problems, some of which are presented in this paper, have shown excellent agreement between OEFPIL and other methods. |