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OVERVIEW
Curve Fitting Solutions Data obtained from experiments usually contain significant variations due to measurement errors. The purpose of curve fitting is to find a smooth curve that on average fits the data points. There is a distinction between interpolation (see menu under)  "Interpolation Solutions", and curve fitting. Interpolation can be regarded as a special case of curve fitting in which the function must go exactly through the data points. Curve fitting is applied to data that contain gaps, usually because of measurement errors and tries to find the best fit to a set of given data. The curve does not necessarily pass through all the given data points. As example of utilization at Keystone Mining Post we show the Straight Line Fit Method and a Polynomial Curve Fitting Method for distinct order-polynomials. Please select from the menu  →         CURVE FITTING SOLUTIONS  (press to select)

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EIGENVALUE SOLUTIONS...
Eigen Inverse Iteration
Rayleigh-Quotient Method

INTERPOLATION APPLICATIONS...
Cubic Spline Method
Newton Divided Difference

 Applied Mathematical Algorithms Complex Functions A complex number z = x + iy, where... Complex Functions Non-Linear Systems Non-linear system methods... Non Linear Systems Differentiation Construction of differentiation... Differentiation Integration Consider the function where... Integration