; This example demonstrates the ability to find
; values for constants in a function that make the
; function best fit empirical data.  Because the equation
; file includes a LEVEL 0 statement, Mercury will
; perform a Least Squares Fit to find the function (of
; the required form) that best matches the points (x, f(x)) given.

; In this example, the function is
;    f(x) := EXP(a * x^N + B)
; where the ideal solution is close to a = 0.25, b = 0.15 and N = 1.5.

f(x) := EXP(A x^N + B)

f(1) = 1.49
f(2) = 2.35
f(3) = 4.26
f(4) = 8.59
f(5) = 19.01

LEVEL 0