9.23 minimize()

Description

Minimize an array in the least squares sense, by adjusting the values of the fitting variables. This gives a simple and flexible way to fit general data to a fairly simple models.

Input Program Variables

None.

Keywords/Values

Keyword	Variable	Default	Description
1array			residual to be minimized
x			x-array associated with array
uncertainty			array of uncertainties in residual
xmin			low-x value for fit range
xmax			high-x value for fit range
toler		1.e-8	fitting tolerance
restraint			scalar fitting restraint

Output Program Variables

chi_square, chi_reduced. For each variable XXX, the variable delta_XXX will be given it's estimated uncertainty.

Notes

The array named by x is optional, and is necessary only if xmin or xmax are given. The array given by uncertainty is optional as well.

Currently, only 1 restraint scalar can be added.

Examples

 
  Iff> guess (a  = 1, b = 0)
  Iff> my.resid = my.data - (a * my.x + b)
  Iff> minimize(my.resid)

See also

feffit()(Section 9.11), Chapter 8.