UCF Physics: AST 5765/4762: (Advanced) Astronomical Data Analysis
Fall 2009 Lecture Notes: 13. General Fitting
1 Check In: 12:30 — 12:35, 5 min
•Questions before we start?
•Level check
2 General Linear Fitting: : — :, 10+5 min
•First example extends the line fit to linear scaling of arbitrary models
•This is a quick-and-dirty method, useful because everyone has a linfit routine
•Take each prediction of a nominal model,
•Multiply by a constant,
•Add another constant
•2 free parameters, like a line fit
•Can use linear fitting routine to find parameters
–Calculate a “nominal” model
–Treat xas the parameter in a parametric equation
–Calculate model for xvalues in data
–Pair those with yvalues in data
–Plot d=ydata vs. m=ymodel
–No error in m, but error in d
–So, dgoes on vertical axis
–Fit a line!
–Slope is how much you multiply model by
–Intercept is how much you add to model
–If model has just multiply parameter, intercept is used as a final background fit
•Can still do if data are in more than 2 axes
•E.g., model depends on xand yin an image
•fitting demo
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