The term "global fitting" generally refers to simultaneous curve fitting operations performed on multiple datasets. Because datasets remain distinct, they may or may not "share" parameter values during the fit process. When a parameter is shared, a single parameter value is calculated for all datasets; When a parameter is not shared, a separate parameter value is calculated for each dataset.
By contrast, "concatenated fitting" is performed by combining all datasets into a single dataset. Because curve fitting operations are performed on a single dataset, only a single set of parameter values is returned.
Since 2016 SR2, an new app Sequential Fit has been released to do sequential fitting on multiple datasets. With this app, the fit parameter values obtained from the current dataset will be used to initialize the parameters of the next dataset. This is very applicable for those datasets, the common parameters of which keep changing in turn.
This tutorial will show you how to: