The best way to fit your multiple peak data depends on the nature of your data, the number of peaks, and what type of fitting function you are using. The following is a general guideline:
1. Does your data have a baseline?
If your data has a baseline that is not zero or a constant, such as say an exponential baseline, then you need to obviously account for the baseline. You then have the following options:
a) If you are running OriginPro 8, you can use the Peak Fit Wizard which will allow you to either define or fit the basline, and then either subtract the baseline or fit the baseline in the final peak fitting process
b) If you are running Origin 8, you could use the Create Baseline tool to create an appropriate baseline for your data and then use the Simple Math tool to subtract the baseline. Once baseline has been subtracted, then you can proceed with fitting your data using other available methods outlined below
2. Does your data have many peaks, such as more than 10 peaks, or does your data have hidden (shoulder) peaks?
If you have many peaks or hidden peaks, it is better to use the Peak Fit Wizard in OriginPro 8 which provides better peak detection methods
3. Does your data have just a few peaks, such as say less than 10, and no hidden peaks?
You have the following options:
a) If you have OriginPro you can of course use the PFW even if number of peaks is not large. The PFW report has many options on what peak characteristics to report, in addition to the fit parameters.
b) You can make use of the "Fit Multi Peaks" menu item. This option allows you to specify the number of peaks and graphically click and specify peak locations. Note that if there is a hidden peak that is somewhat obvious you can click and specify the expected peak centroid and this method could work with such hidden peaks. This option is however limited to Gaussian and Lorentzian functions. Also, the report sheet is limited and does not current have customization options on what to report.
c) You can use the NLFit tool and use the Advanced panel and specify number of replicas. If you have n obvious peaks in your data, specify replicas=(n-1). The peaks will be automatically found and initialized. You will have finer control over the parameters, the fitting process, and you can customize the output. This option is however limited to built-in peak functions and is not available for user-defined peak functions.
d) Create a graph of your data and use the Regional Data Selector tool to define multiple ranges in your data, each range corresponding to one peak. The peaks need to be clearly separately, and the ranges could have overlap such as overlapping part of the baseline for instance. Once you have defined the ranges, open the NLFit tool and the tool will automatically recognize the multiple ranges. You could then set the Multi-Data Fit Mode drop-down to Global Fitting, which will then allow you to share parameters such as say a common y offset.