Origin's NLFit tool is powerful, flexible and easy to use. The NLFit tool includes more than 200 built-in fitting functions, selected from a wide range of categories and disciplines. If the function that you need isn't included, you can define your own function using Origin's flexible Fitting Function Builder.
Operations are usually performed quickly and easily, using Origin's interactive fitting tools:
Fit with Built-in Functions
Origin offers nearly 200 built-in fitting functions. Each built-in function includes automatic parameter initialization code that adjusts initial parameter values to your dataset(s), prior to fitting.
With just a few clicks, you can perform curve fitting and obtain "best-fit" parameter values. You can opt to have the best fit curve pasted to your original data plot:
Fit with User-defined Functions
Can't find a suitable fitting function in the built-in function library? No problem. You can easily define custom fitting functions for use in nonlinear fitting.
The Fitting Function Builder wizard can help you define a custom fitting function:
Fit with Multiple Datasets
Do you have multiple datasets that you would like to fit simultaneously? With Origin, you can fit each dataset separately and output results in separate reports or in a consolidated report. Alternately, you can perform global fitting with shared parameters; or perform a concatenated fit which combines replicate data into a single dataset prior to fitting.
See the list below for supported multi-data fit mode:
Global fit with shared parameters
- Concatenate fit for replicate data
- Independent fit for multiple curves
Need to fine-tune your curve-fitting analysis? With Origin, you have full control over the curve-fitting process:
- Least square fit with Y weight (e.g. error as weight)
- Use parameter bounds and/or linear constraints
In addition to the basic fitting options, you also have access to extended options for more advanced fitting. Note that some options are available only in OriginPro:
Fit with convolution
Orthogonal Distance Regression with X and/or Y weight
Do you need to fit an implicit function to your data? Origin's NLFit tool supports implicit fitting using the Orthogonal Distance Regression (ODR) algorithm, including fitting with X and/or Y error data.
To perform an implicit fit, you generally follow the same procedures that you do when fitting with an explicit function:
Having trouble deciding which function works best with your data? Want to evaluate which data better fits a particular model? OriginPro's fit comparison tools make your work easier:
- Fit and rank all functions in a category
- Compare two fitting models to one dataset
- Comparing two datasets with one fitting model