I'm a perspective Origin user with the following question.

I'm interested in globally fitting (non-linear least-squares) >2 data sets acquired using different experimental means, _on the same experimental system_. E.g., say there are 4 parameters of interest, p1, p2, p3, p4, that characterize a system. One experimental approach gives info on p1 and p2 (dataset A, equation A). Another gives info on p1, p3 and p4 (dataset B, equation B). And a third gives info on p2 and p4 (dataset C, equation C). Is there any way to globally link and fit these data sets, using the 3 equations that describe the separate datasets?

Your help and expertise would be greatly appreciated. If Origin could do this, I may purchase it so I wouldn't have to write my own program to do it!

Erik,

Origin has the ability to fit multiple independent variables (i.e. multiple equations) and share parameters between them. An example of how to do this is described for two dependent variables in the following Technical Review article:

Using the Nonlinear Curve Fitter for Simultaneous Fitting - http://www.originlab.com/www/online_tech_monthly/Sept98/index.asp

Give it a read-through and let me know if you have any questions.