Power Fit Coefficients VI

Owning Palette: Fitting VIs

Requires: Full Development System

Returns the amplitude and power of the power fit for a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.

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	Y is the array of dependent values. Y must contain at least two points.
	X is the array of independent values. X must be the same size as Y.
	Weight is the array of weights for the observations (X, Y). Weight must be the same size as Y. Weight also must contain non-zero elements. If an element in Weight is less than 0, the VI uses the absolute value of the element. If you do not wire an input to Weight, the VI sets all elements of Weight to 1.
	tolerance determines when to stop the iterative adjustment of amplitude and power when you use the Bisquare method. If the relative difference of the weighted mean error of the power fit in two successive iterations is less than tolerance, this VI returns the resulting amplitude and power. If tolerance is less than or equal to 0, this VI sets tolerance to 0.0001.
	method specifies the fitting method. 0 Least Square (default) 1 Least Absolute Residual 2 Bisquare
	amplitude returns the amplitude of the fitted model.
	power returns the power of the fitted model.
	error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster.

Power Fit Coefficients Details

This VI is similar to the Power Fit VI but does not return the y-values or weighted mean error of the fitted model.